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Last Thursday, we proudly inaugurated our new office in Seville. Our Director, Juan Arévalo, led the event with a presentation that reflected on our company's history, achievements and set the stage for our future aspirations.

At Randbee Consultants, we are committed to leveraging data to drive insightful decision-making processes. Our service offerings span a wide range, including statistical analysis, web visualization techniques, spatial modeling, e-learning, and capacity development. We've established ourselves as pioneers in crafting data-driven solutions, consistently adding value across various sectors and addressing the digital divide in developing countries.

Juan highlighted our diverse and impactful client portfolio, showcasing how our focus on innovation and research has created significant impacts in numerous industries. He also praised our team's proficiency in transforming complex data into tangible, user-friendly solutions.

A focal point of our new Seville office, as Juan elaborated, is to foster a culture of collaboration. We are dedicated to making this space a community hub, where we will organize training sessions, events, technological meetups, and hackathons. Our goal is to turn our office into a vibrant meeting point for those passionate about sustainability and data in Seville.

Concluding the presentation, Juan outlined the challenges and goals ahead for Randbee Consultants. Our new office, located at [https://maps.app.goo.gl/5y9WtwFkkt94tjtW8](https://maps.app.goo.gl/5y9WtwFkkt94tjtW8), is envisioned to be more than just a workplace. It will serve as a dynamic community space, aligning with our mission to lead in the information age through continuous innovation and community engagement.


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Last Thursday, we proudly inaugurated our new office in Seville. Our Director, Juan Arévalo, led the event with a presentation that reflected on our company's history, achievements and set the stage for our future aspirations.

Exciting News: Celebrating Our New Office in the Heart of Seville!

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Ever wanted to solve a real-world problem in 48 hours? Hack, and marathon. Two seemingly unrelated words that when put together describe one of the most innovative and cutting-edge methods to help solve real-world complex challenges over a short space of time. At Randbee Consultants, we have co-organised three hackathons to date which is no mean feat. Co-organising such diverse and multifaceted hackathons allowed us to tackle a unique set of challenges from logistical organisation to providing dynamic training and engaging innovation workshops. Despite these challenges we surpassed all expectations, and the hackathons were a resounding success; a real testament to our ability to foster innovation and sustainability. 

Hackathons are becoming increasingly popular in the tech and business sector, with many organisations adopting this method to explore new avenues to unleash innovation and creativity. Furthermore, in a rapidly evolving world where sustainability is no longer a niche concept but a necessity, many hackathons are now focused on finding solutions to problems centred around sustainability, allowing companies and individuals to meet their environmental and social responsibilities. 

#### Benefits of Participating in Hackathons

Hackathons offer a whole host of benefits for participants looking to get involved, such as:
- **Skill enhancement:** Hackathons thrive on unconventional thinking, propelling participants way beyond their comfort zones, driving innovation and personal growth.
- **Networking Opportunities:** Hackathons typically attract a diverse crowd of like-minded individuals, allowing ideas to be shared and new synergies to be formed.
- **Real-World Problem Solving:** Hackathons often tackle real-world challenges, and in our case challenges with sustainability at the forefront.
- **Prizes and Recognition:** From project recognition to cash prizes, coaching programmes, technological devices and job offers, the variety of prize packages on offer are endless.

Not only do the participants of hackathons have a lot to gain but so do the sponsors, partners and mentors. Getting involved in a hackathon allows companies to tap into the creativity and problem-solving skills of participants, identifying potential future employees and partners and gaining new ideas or solutions for their own products and services. Furthermore, hackathons offer visibility to sponsors and partners, allowing them to promote their own services and expertise, whilst also allowing companies to give something back to the tech community. For instance, our experience of mentoring and co-organising hackathons is our way of doing just this which has given us a great sense of satisfaction and fulfilment.

#### Overview of Our Hackathons

The [Copernicus Hackathon Malaga](http://copernicus.adabyron.uma.es/cophackmalaga/), for example, was an online event and focused on blue and green sustainability to help mitigate the effects of the climate crisis felt in the city of Malaga and further afield in the Mediterranean by developing a solution utilising Copernicus data. Participants collaborated for 15 days in diverse teams of 4 or 5 people, with the end goal of finding solutions to challenges such as how to use Copernicus data to address: green and smart cities; sustainable and smart tourism; sustainable blue growth; and to respond to the consequences of Covid-19. The [Oman Earth Observation Hackathon](http://eohackathon.adabyron.uma.es/) also kept sustainability as a core theme using Earth Observation Data but with very different challenges, focusing on disaster risk reduction, the oil and gas sector, surveying and mapping, and water and agricultural applications. Participants worked in groups of 4-6 people over 2 full days in a mission to develop a solution to these challenges with commercial value . Equally championing sustainability, Climathon is the world’s largest climate innovation hackathon with [Climathon Seville](https://linktr.ee/Climathonsevilla) focusing on the phenomenon of heat islands in shared urban spaces in response to increasing record breaking temperatures. Teams had 48 hours to develop a solution and bring together a wide group of local communities with the end goal of promoting a Seville that is more resilient to climate change.

#### Success Stories

Great things emerge from Hackathons such as landing a dream job, the creation or the propulsion of successful start-ups, and projects that evolve into real products. For example, the start-up YNSAT was created at the online Copernicus Hackathon Malaga. This start-up aims to make satellite data available to everyone by providing useful information about the planet in an accessible format. Furthermore, during Climathon Seville 2021, the Remonda project was born with a mission to transform the more than 5 tons of oranges that the city of Seville generates every year into biomaterials. The project aims to give organic waste a second life, whilst also creating value added products that are bio-based, biodegradable, and locally produced, thereby replacing the use of conventional plastic. 

#### Our Expertise

In order to successfully co-organise these hackathons, we made it a priority to open the hackathons to anyone interested, offering an inclusive, engaging and productive hackathon experience for all involved. Welcoming this diversity encourages a rich environment for creativity and problem-solving, ensuring we deliver unique events that maximise innovation. 

 During the preparatory sessions and throughout all hackathons, we offered comprehensive **training on utilising Copernicus data and services**. Our carefully curated agenda included detailed organisational logistics and a program designed to maximise participant engagement and learning. Highlights included dedicated sessions and presentations focused on **mastering the art of pitching,** complete with valuable tips and tricks to allow participants to craft the perfect pitch. Additionally, we facilitated mentoring groups aimed at further developing participants' ideas, guiding them through the **creation of a robust business model canvas**, and assisting in the development of a **minimum viable product (MVP)**. Additionally, mentoring allowed us to provide **useful insights from our own personal experiences** which is a truly indispensable contribution to the participants and to the event. This is also reinforced by team Climathon Seville who viewed our role as invaluable:

> "Randbee Consultants played a key role as a mentor during the Climathon Seville 2023. Randbee provided technical and business-oriented assistance to all the participants on the development of their projects over the course of the weekend. We at team Climathon Seville are thrilled that Randbee Consultants ethos is aligned with our main objective: society’s sustainable development; and we are very excited to be planning future Climathon events where we will be looking to collaborate with Randbee Consultants again." - **Team Climathon Seville**

#### Conclusion

Hackathons are a key component of the tech ecosystem, and whether you’re a newbie or a seasoned professional, 2024/2025 promises to be a great time to get involved either as a participant, sponsor or partner. Partnering with Randbee Consultants will help bring transformational ideas to actionable solutions as we are committed to using our expertise to make hackathons as revolutionary as possible. As a forward thinking company, we view a hackathon as not just an event: it’s a step towards a more sustainable future. Will you join us?

###### Following the success of our last three hackathons, we are already planning our next event and we will be revealing more details shortly. Follow us on our socials and contact us [here](https://randbee.com/contact) for more information. Let’s collaborate to foster innovation and drive real change together!


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Ever wanted to solve a real-world problem in 48 hours? Hack, and marathon. Two seemingly unrelated words that when put together describe one of the most innovative and cutting-edge methods to help solve real-world complex challenges over a short space of time.

Our Hackathon Journey: Fuelling innovation and sustainability

The digital ecosystem is constantly evolving, and companies are looking for ways to adapt and streamline their processes to keep a competitive edge. Using a custom R package is a way of achieving this, and at Randbee Consultants we pride ourselves on our expertise in R scripting and package development. We have been involved in numerous international projects showcasing how a customised R package can propel your business. 

The goal of this blog post is to describe why companies and statistical offices in particular may need and benefit from a custom R package; how to develop an R package, including the practical steps involved; and further explore Randbee’s role and expertise in the development of custom R packages. 

### The Need for R Packages in Statistical Offices and Beyond

R is a statistical programming tool that’s well equipped to handle large amounts of data. R lends itself to performing a variety of tasks, including data manipulation, mining and modelling whilst promoting versatile presentation capabilities. Its use in statistical analysis has been widespread, with data scientists, statisticians and researchers, amongst others, relying on R for various tasks. Furthermore, the adoption of R has been significant worldwide by corporations and statistical offices.

R allows statistical offices to use robust data analysis which is key to the reliability, accuracy and consistency of statistical modelling and data analysis. More specifically, by embracing R packages, statisticians can elevate their analytical capabilities allowing them to better contribute to evidence-based decision-making.  For many companies, statistical software maintenance and deployment are also essential to ensuring that software continues to meet customer needs, remains compatible with other technologies and complies with regulatory requirements. In this sense, R is used to deploy and maintain statistical software which helps foresee and mitigate future issues and is indispensable for maintaining resilient and high performing software ecosystems. 

Statistical offices and companies without a dedicated R package often encounter common issues such as inefficiency, increased error rates, inconsistent data interpretation and representation, and poor product outcomes. This will be explored in further detail below:

### Benefits of Creating a Customised R Package 
***Increased efficiency:*** Creating a custom R package can avoid repeatedly creating similar plots or visualisations by automating the process. Furthermore, an R package allows the user to encapsulate plot features within custom functions, eliminating the need to manually specify aesthetics and alignment each time, thus saving valuable time.  

***Customised Data Visualisations:*** R libraries allow extensive customisation, allowing the user to tweak colours, labels, scales and much more. Therefore, creating a customised R package enables the company to create visualisations tailored to their specific needs; graphs can be as detailed or straight forward as the company requires and they can adhere to a specific design or branding.

***Quality Assurance:*** When an R package is created, the functions are documented which enhances their quality. Furthermore, proper documentation makes it easier for other team members or partners to understand and use the package effectively. This promotes knowledge sharing and best practices, fostering collaboration and streamlining workflows. 

***Decreased Error Rates:*** Statistical analysis requires a high level of accuracy and precision to enable reliable results. Using a dedicated R package can maintain consistency and standardisation in data collection procedures, data cleaning and preprocessing, and statistical methods and assumptions.

***Tailored Functionality and Data Privacy Standards:*** Creating an R package allows the designer to customise functions to meet unique organisational needs. For example, if the customer deals with economic data, functions can be created that calculate specific economic metrics. Furthermore, functions can also be tailored to control data access and enforce privacy standards, ensuring that sensitive data remains within a secure space. 

### How to Develop an R Package 

#### First Stage: Functions and Features

***Identify Needs and Functions:*** In order to create an R package, it is wise to consider what the purpose of the package is; what problem does it solve? This helps to ensure the functions and features are aligned with the users needs in mind.  Extensive tasks justify sophisticated frameworks with several functionalities that form a cohesive package.  

***Package Structure:*** Start by setting up the relevant files and directories for the R package. To create the basic structure, tools such as create_package() can be used. The basic structure of the package includes directories such as **R/, man/, data/** and files such as **DESCRIPTION and NAMESPACE**. It is also crucial to consider package versions to ensure compatibility and maintain a robust package. The package's **description** file is where compatible versions can be specified and following this, the package can then be tested to ensure stability. 

***Write and Document Functions:*** Write the functions with the **function** keyword in the **r/** directory and then write the necessary documentation (**function descriptions, examples, and vignettes**) using **roxygen2**. The components of a code are made up of the following: Function name, parameters, and function body, for example: ** my_function <- function(parameters) {**.  It is worth noting that well documented functions improve code readability and it is also worth considering using **object-oriented programming (OOP)** principles to organise the code. 

#### Final Stage: Testing and Validation

***Testing:*** After developing a custom R package, the testing and validation stage is an essential component where every line of code should be tested before release. QA experts will then use manual and automatic testing to detect and fix potential bugs, ensuring software is in the best condition it can be for release. Usability testing should also be incorporated into the quality assurance process as testing the design before it goes into development increases confidence that the product is of high quality. This will also ensure usability and accessibility issues are caught early in the process and avoid any costly fixes down the line. Furthermore, developing a prototype can prove valuable for testing ideas, getting feedback and refining the package before the final release. 

***Stakeholder Feedback:*** Participation and feedback from stakeholders is another crucial step and regular contact should be maintained with the client throughout the process. Enhanced communication will lead to greater agility, making incorporating changes and adapting to evolving market needs or stakeholder feedback easier.

***Reliability and Performance:*** It is essential to ensure the reliability and the performance of the package by putting certain methods in place such as proper maintenance, controlled releases and identifying any issues that need addressing. Adding a licence to the package is also crucial to protect the product. 

***Ongoing Support:*** Support after the product launch is the final step in the process to ensure the product stays relevant and delivers high performance. Continuous integration and deployment practices will be applied for ongoing product improvements. 

### Randbee’s Role and Expertise

Randbee has a wealth of experience relating to R package development and has successfully worked on multiple projects using R alongside Machine Learning, statistical analysis, web visualisation techniques, modelling, and capacity development. We have worked with organisations such as the United Nations, the European Commission, as well as universities and international governmental bodies. Our recent project with Eurostat is detailed below, which allowed us to showcase our expertise in R package development and highlights how a customised R package can benefit your business in multiple ways. 

#### Case Study: An R package to easily create html dashboards by non-expert R users: a Eurostat tool for short-term economic analysis

Storytelling to show the macro-economic situation through meaningful indicators is critical for statistical institutions such as Eurostat.  Eurostat developed an R script using the R markdown language with additional functionalities of the Flexdashboard package which created interactive charts using the Plotly package. Whilst this addressed the need for a more streamlined dissemination of official statistics, improvements in the design were needed to make the tool more flexible and adaptable. This is where Randbee’s expertise helped to make various improvements to the previous tools script, enhancing its layout, accessibility, performance and usability, including options to make it more customisable and to extend its functionalities. Randbee has created a new R package to increase readability and efficiency, as well as to optimise the speed and performance of the website. The new package is a highly friendly tool which allows any R user to create their own dashboard, customise it and include their own data and descriptions to be visualised in multiple formats (line and bar plots, tables, maps, amongst others).

> The new package called **eurostatRTool** has been positively assessed by experts from several National Statistical Offices across Europe as well as by Eurostat, proving its usefulness and its ease of use.

At Randbee Consultants it is our priority to offer a comprehensive and holistic approach when developing an R package with clients such as Eurostat. We provide comprehensive support from the initial ideation and conceptualisation to deployment, maintenance and evolution; ensuring that every phase is interconnected, allowing for seamless transitions between stages. This approach prevents disjointed development such as inconsistent communication and disappointing project outcomes. 

### Conclusion

A customised R package has many advantages such as reducing error rates, increasing efficiency and customised data visualisation options. Statistical offices in particular often deal with a unique set of challenges and a custom R package allows them to create specialised tools tailored to their specific needs, benefitting data analysis and workflow. However, developing an R package is no mean feat and requires planning, documentation and testing, and ongoing maintenance and updates. Randbee Consultants can help you build the right tools to outpace the competition and adapt to the changing digital landscape. We will provide unmatched holistic technical expertise by using our skills and experience to create a unique environment for success across the full product development lifecycle and beyond. So why not get in touch [here](https://randbee.com/contact) to start your customised R package journey with us and enhance your data analysis capabilities.

At Randbee Consultants, we are a data driven company, simply meaning; we love data! We are experts in leveraging data to support our work and we offer a variety of data led services such as statistical analysis, web visualisation tools, modelling, machine learning and all things R related. Check out our [projects](https://randbee.com/projects) page to see more successful solutions developed by Randbee and follow us on our [socials](https://twitter.com/RandbeeCo) to keep up to date with our latest ventures!

We don’t just write code. We solve complex data problems.


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The digital ecosystem is constantly evolving, and companies are looking for ways to adapt and streamline their processes to keep a competitive edge. Using a custom R package is a way of achieving this, and at Randbee Consultants we pride ourselves on our expertise in R scripting and package development. We have been involved in numerous international projects showcasing how a customised R package can propel your business. 

Why you need a custom R Package for your business and how to get one

We live in a digital era where data is often referred to as the new oil. Just like oil, data is precious however, it is useless in its raw state. Data needs to be extracted, refined, and transformed before organisations can harness its true potential. 

Data is a valuable resource and proper data management can unlock an organisation's potential for success. This blog post will explore what data management is, the challenges with data management, and how it can be transformed and used effectively including a case study detailing how Randbee Consultants successfully developed and maintained Data Management Plans (DMP) for EU funded projects.

Data management is the practice of collecting, organising, protecting, and storing an organisation's data (and their associated metadata) so it can be analysed to help make better business decisions. It involves multiple tools and processes to ensure the data is accurate, accessible, and secure and up to date. Data management is a crucial component of an organisation's ability to thrive, however, managing large datasets presents several key challenges outlined below.

### Data Management Challenges

***Data storage:*** Ensuring data is stored efficiently is crucial and large data sets require substantial storage capacity, which can be expensive.
 
***Data Quality and Integration:*** Inconsistent and inaccurate data can lead to poor decisions. Combining data from different sources can also be difficult as data can come in different formats and structures.

***Scalability:*** A growing business will need to scale its data management systems accordingly. A rapid increase in data volumes and data complexity can be challenging. 

***Data Security and Privacy:*** Ensuring compliance with data protection regulations and ensuring data is secure from unauthorised access and breaches is crucial. 

***Data Querying:*** Involves requesting specific information from databases and is a crucial yet challenging process in data management. 

***Visualisation:*** Specialised techniques and tools are needed to effectively present and visualise (via maps and graphs) large datasets.

### Our Expertise in Data Management

Randbee Consultants has extensive experience working with global organisations which has allowed us to develop an impressive portfolio of [work](https://randbee.com/projects), showcasing our ability to create successful and impactful large-scale projects. For example, we have created and implemented multiple data management projects specifically tailored to the academic, governmental, and commercial sectors. For example, the below case study highlights two EU funded Horizon 2020 projects where Randbee was in charge of the data management. 

#### Case Study: PONDERFUL and AQUACROSS EU Funded projects:  Design and Implementation of a Data Management Plan (DMP) to propel them into success 

Randbee was tasked with creating a DMP to support two Horizon 2020 projects. The DMP included the creation of a CKAN-based data platform to ensure the data generated in the projects is findable, accessible, interoperable and reusable (FAIR).  [PONDERFUL](https://ponderful.eu/) focuses on the use of ponds as nature-based solutions for climate change adaptation and mitigation, and [AQUACROSS](https://aquacross.eu/) aims to support the EU efforts to protect aquatic biodiversity and ensure the provision of aquatic ecosystem services. Therefore, the data platform designed and implemented by Randbee, which brings data from both projects together, provides multiple resources in the field of aquatic research to a wide range of potential users, from the general public to technicians and scientists. 

Data management within the framework of both projects presented quite a challenge due to the broad scientific and geographical project scopes, the multiple case studies and the vast amounts of specialised data required. Posing further challenges is the need to effectively manage and share data from various project partners, to ensure consistency in quality across various data formats and sources, and finally, to ensure clear communication among multiple partners. 

The Plan implements procedures for data collection, storage, access, sharing, and quality control. The DMP also served to support conducting translational research including several collaborative and interdisciplinary research programmes. Due to the project’s complexities, Randbee addressed common concerns and worked closely with partners to ensure any issues were dispelled. For example, privacy restrictions were a topic of concern however Randbee applied the principle of “as open as possible, as closed as necessary”. This means that data sharing can be restricted when legitimate reasons exist.

> "This project showcases our multifaceted approach to handle complex data and customise CKAN to specific projects, allowing organisations to unlock valuable insights that can drive innovation and sustainability. In this digital age, organisations have a multitude of data, however, success doesn’t rely on data collection- it relies on data management and insight - **Juan Arevalo, CEO Randbee Consultants**

Despite the complexities, Randbee Consultants used their in-depth knowledge and experience to develop and implement a comprehensive Data Sharing Information Platform. The projects’ data strategy relies on this data platform, to facilitate an easy electronic access (under copyright and intellectual property constraints), to the wide range of data types generated in both projects, and for a diverse group of data users requiring different levels of interpretation. The data platform is based on Comprehensive Knowledge Archive Network (CKAN) software, an open-source framework for developing open data portals, which provides a reliable entry point for all data and metadata collected, processed or analysed by the project.

The platform also facilitates seamless data integration and sharing among project partners and provides open access to a wide range of resources related to marine, freshwater and coastal ecosystems, focusing on data from the projects Demo Sites and Case Studies, and the proceeding maps, model outputs and tools. 

### CKAN as a Data Management Tool

The Comprehensive Knowledge Archive Network (CKAN) is an open-source data management system designed to facilitate the storage, distribution, and management of open data. CKAN powers many organisations and government open sites as it makes it easy to publish, share, and use data by providing tools that streamline these processes

We at Randbee Consultants have a wealth of experience in implementing and customising CKAN for numerous international data management projects. We focus our expertise on developing data portals using open-source technologies like CKAN, which adds value to our data management projects by increasing the impact of the project. For example, our mastery in CKAN led to the development and deployment of the data management for PONDERFUL and AQUACROSS (mentioned above). The data strategy in both projects are based on CKAN software, allowing us to tailor the system to the projects’ needs and provide a technical solution with a reliable entry point for all data and metadata collected, processed, or analysed by the projects. Tailoring CKAN allows the projects to provide open access to a wide range of resources related to aquatic ecosystems, mostly at the European level.  Finally, we are able to showcase our technical ability in implementing and customising CKAN in these projects by ensuring research data is available without restrictions on access or re-use, enhancing the visibility and interpretability of users and with other environmental information platforms. 

### Developing Data Management Plans (DMP)

A well-defined and well-structured DMP ensures that an organisation adheres to relevant data protection laws and regulations, which in turn helps to avoid legal penalties and strengthens trust with stakeholders. Furthermore, implementing a structured DMP streamlines data workflows, making it easier to manage data throughout its lifecycle. This includes data acquisition, processing, storage, and disposal, enhancing overall efficiency. In order to produce a successful DMP, there are a few key components to include:

***Statement of purpose and data definitions:*** It is essential to outline the objectives of the data management activities, explaining why different data is being collected and how it is being used.  Furthermore, clear definitions and descriptions of the data, including naming conventions, metadata standards, and data formats, ensure consistency and understanding amongst all stakeholders. 

***Data Collection, Storage, and Security:*** This includes details on how data will be collected, stored, and accessed, including information on data sources and methods of data collection. Strategies for securely storing data, including backup procedures, encryption methods, and access restrictions all protect sensitive information. 

***Data Sharing and Reuse:*** This includes guidelines for sharing data with researchers or stakeholders, including any restrictions or permissions required, and also covers methods of data reuse in future projects.  

***Data Preservation and Monitoring:*** It’s essential to ensure the long-term preservation of data so that it remains accessible and usable over time. This can be achieved by archiving procedures and formats. Regular monitoring and review of the DMP ensure it remains effective and up to date, often requiring periodic audits and updates as needed.

When creating a DMP for EU project requirements and research centres standards, our methodology involves several specific considerations. In particular, we ensure that the DMP is well structured as this is key to achieving a successful and effective plan. Firstly, the DMPs need to ensure that data is managed according to the FAIR principles (mentioned above). We also ensure that the DMP aligns with any institutional requirements. Following the project overview, we discuss and analyse the different types of data collection and production and outline metadata standards. This ensures that data is well-documented and easy to understand. EU projects and research entities often require that data be made openly accessible unless there are legitimate reasons for restricting access, which we discuss in depth with the client before including in the DMP. We also outline information on data licences, embargo periods, data storage, quality assurance, data privacy (especially under regulations such as GDPR), intellectual property rights, data ownership and any ethical aspects of the project. 

The final considerations include implementation and monitoring, both of which must adhere to the customised details outlined in the DMP. Regular review and updates are often necessary to reflect project changes or new requirements from EU funders or the institution. 

### Innovation in Data Management

As technologies are constantly evolving, DMPs are able to integrate more sophisticated tools to leverage data. For example, advanced analytics to analyse trends and patterns continues to accelerate, which allows organisations to identify opportunities for improvement and innovation. Furthermore, AI and machine learning to automate processes and enhance data analysis is another tool constantly evolving; Artificial Intelligence (AI) can reduce manual efforts as it automates tasks such as data cleaning, transformation, and integration; it can introduce predictive analytics as AI algorithms can analyse historical data to predict future trends, allowing organisations to make proactive decisions; and Natural Language Processing (NLP) can be used to extract insights from unstructured data sources such as text documents, emails, and social media. Finally, development in open data practices ensures data is freely available to everyone, promoting transparency and innovation. For example, sharing data across organisations can lead to collaborative efforts and lead to new insights and solutions. By using standardised formats and protocols, open data can be easily integrated and used by different systems. 

Randbee leverages data management to fuel innovation and sustainability by integrating several innovative approaches and targeted solutions into data management strategies. For example, In-house knowledge and data can sometimes be difficult to find as they can be kept in different silos. This limits data sharing and re-use; leads to a duplication of sampling and analysis efforts; and leads to inconsistencies of the data with other data sets. Our solution involves global archiving, accessing and preservation of data including developing a data portal, organising data by topic and data source, and implementing trusted general-purpose repositories. Our ability to strategically leverage data allows organisations to drive both innovation and sustainability, leading to long-term benefits for the business and the environment. This sharing of data and insights with partners and stakeholders can foster collaboration and lead to innovative solutions and collective efforts toward sustainability. 

### Conclusion

[Randbee Consultants’](https://www.linkedin.com/company/randbee) vision for the future of data management is transformative, driven by many advancements in areas such as AI and machine learning. Furthermore, with increasing data regulations and privacy concerns, robust data frameworks will become essential. This includes ensuring data quality, compliance, and ethical use of data. To make projects more widely available to a larger audience, data democratisation is also essential. Making data accessible to a wide range of users will be our priority and involves integrating user-friendly tools and platforms using open-source technologies such as CKAN to allow non-technical users to derive insights from data. We believe that the future of data management is more intelligent, secure, and integrated, ultimately enabling organisations to leverage data more effectively for innovation, decision-making, and sustainability.

If you’re looking to transform your data into insights and not be bogged down by inefficiencies, then get in touch with us [here](https://randbee.com/contact) and we can discuss how to leverage your data to unlock your organisations true potential. Our tailored data management solutions can streamline your operations and offer a way forward into a more agile, data-driven future. Learn more about [Randbee Consultants](https://randbee.com/about-us) and follow us on our [socials](https://x.com/RandbeeCo) to see what we get up to! 








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We live in a digital era where data is often referred to as the new oil. Just like oil, data is precious however, it is useless in its raw state. Data needs to be extracted, refined, and transformed before organisations can harness its true potential. 

Leveraging Data Management: The key to unlocking an organisation's success

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*Image: The Copernicus ECMWF migratory bird interactive [storytelling tool](http://birdmigration.service.compute.cci2.ecmwf.int/the-progression-of-bird-migration), developed by Randbee Consultants, showcasing spring bird migration movements.*

It’s widely believed that data is one of the most powerful mechanisms for telling stories. However, how can you create a story with numbers I hear you ask? The key is to weave that data into a compelling narrative that will resonate with individuals, just like any other good story you’ve read before. 

Data storytelling is the concept of creating a captivating narrative based on complex data and analytics that tells a story to influence and inform a particular audience. Web based storytelling tools are used to help to create these engaging narratives and combine data visualisation with text, graphics, and interactive elements to make complex information more accessible and memorable, leading to better understanding among the general public, but also among certain professionals such as policy and decision-makers.  

###  Advantages of data storytelling

In many ways, data storytelling is similar to human storytelling but enriches the narrative further by providing deeper insights and supporting evidence through graphs, maps, pictures, videos, animations and audios. Some benefits of successful data storytelling are:

- **Enhanced understanding:** Presenting data in a narrative format enables complex information to become more accessible and relatable, making it easier for broad audiences to grasp key points. 
- **Increased engagement and connection:** Stories are naturally more engaging than raw data, making it easier to retain information and make the data more memorable. Having a narrative also makes it easier to connect with on a human level. 
- **Informed Decision-Making:** Insights and trends are highlighted by data storytelling, aiding in quicker and more confident decision-making. 
- **Credibility and Influence:** Effective data storytelling can establish a business as a thought leader in the industry, building credibility and influencing a particular audience. 
- **Actionable Insights:** Based on the insights presented, it becomes easier to inspire action and drive change by clearly communicating the story behind the data. 

### Key elements to data storytelling

**Data:** This is the foundation of the story and therefore crucial to get right. Ensure data is accurate, relevant, and comprehensive. This involves thorough analysis using techniques such as descriptive, diagnostic, predictive, and prescriptive analytics. 

**Narrative:** This is the storyline that guides the audience through the data. It provides context, highlights key insights, and connects the data points in a meaningful way. A strong narrative consists of characters, setting, conflict, and resolution (this is explored further below). 

**Visualisations:** Effective visualisations help to reveal patterns, trends, and insights that aren’t necessarily obvious from raw data. This includes graphical elements that make data more accessible and engaging such as charts, graphs, and infographics. 	

**Delivery:** The way the data story is presented is essential. Some elements to think about include the medium (e.g., reports, presentations, dashboards) and the manner of delivery (e.g., in-person, virtual). Tailor the delivery to your audience to maximise impact and generate a response. 

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*At Randbee Consultants, we combine all of the above elements when creating a data story therefore generating a strong emotional response from our audience. By framing data within a story, we make the information more relatable and memorable. This emotional connection can motivate the audience to take action and make informed decisions based on the insights presented.*

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### Web-based map tools combined with narratives

Web-based map tools combined with narratives allow the user to create interactive and engaging stories by integrating maps with multimedia elements such as text, images, video, and audio. They are particularly useful for presenting complex data in an accessible way, to target non-technical audiences. Furthermore, they contain functionalities that enable users to interact with them, enhancing user engagement. Maps also provide a geographical context that can be critical for understanding certain narratives, for example showing environmental changes or the location of historical events and patterns.

### How Randbee Consultants crafts a compelling data narrative

As mentioned above, data storytelling is based on the same narrative elements as any other story: characters, setting, conflict, and resolution. For example, The Copernicus ECMWF (European Centre for Medium-Range Weather Forecast) migratory bird [storytelling tool](http://birdmigration.service.compute.cci2.ecmwf.int/the-progression-of-bird-migration) on Bird Migration that we developed with Fundacion Migres, analyses the effect of climate variations on bird migration and can be used to illustrate how we craft a compelling data narrative to inspire change:

1. **Characters:** Migratory birds take centre stage as the key characters, with other stakeholders consisting of ornithologists, bird lovers in general, the general public (to help raise awareness of the particular effects and the importance of global warming), policymakers, and the Climate Change Service (C3S- one of the six thematic services provided by the European Union's Copernicus Programme) products, to increase user uptake. 
2. **Setting:** We set the scene by highlighting that migratory birds are considered bioindicator species and therefore can be used to identify the environmental consequences of climate change across the globe. It also was essential we used data to show how bird migration patterns have changed over time. 
3. **Conflict:** This is where the fundamental issue is described: An overwhelming amount of evidence has been generated which highlights the negative impacts of climate change on ecosystems, habitats and species, including the timings and ranges of bird migration patterns. 
4. **Resolution:** This is where the solution is proposed. We analysed different ERA5 climate data products (e.g., air temperature, precipitation, wind speed, and direction, etc.) to measure the environmental factors modifying migratory bird behaviour. Furthermore, machine learning techniques such as Random Forest, as well as complex and flexible multivariate modelling approaches, such as Generalised Additive Models, were applied to relate the environmental predictors to the occurrence of migrating birds across Europe over time. As a result, we created a visual [storytelling tool](https://birdmigration.climate.copernicus.eu/) that showcases 1) the geospatial exploration and visualisation of the progression of the bird’s migration during spring and 2) the changes in bird migration patterns over the last 40 years, in a clear and captivating manner. The visual storytelling tool introduces a showcase species and demonstrates how bird migration is changing across different regions in Europe as a consequence of climate and other human-induced changes, ultimately raising awareness to a broad audience and inspiring change. 

### How Randbee uses storytelling to deliver impactful solutions

In addition to creating a compelling narrative, we are experts in developing web visualisation tools. We thrive on translating raw data into derived spatial information for education, conservation and decision-making, including the development of web storytelling and visualisation tools. Our ability to develop web-responsive applications brings complex, scientific results closer to the general public through captivating online narrative tools, raising awareness on pressing environmental issues, and more. Through our storytelling web tools, we provide innovative solutions and add value by creating new mapping products from spatial data. 


> "By combining captivating visualisations such as story maps with emotional narrative, we are able to successfully engage people with a story that they don’t just read, they feel, allowing us to craft stories that resonate in a way that raw data simply can’t." - **Beatriz Martin - Project manager, Randbee Consultants**

To highlight this, below you will find some examples of our projects that showcase our involvement in storytelling tools to deliver impactful solutions to complex problems. 

### Case Studies

**1. Marine Spatial Planning (MSP) Global Storytelling Tool**

![image2.png](https://randbee.com/strapi/uploads/image2_77e287f84f.png)

**[Check out The Western Mediterranean MSP Global Storytelling Tool Here](https://storytelling.mspglobal2030.org/westmed/?lang=en)**

**[Check out The Gulf of Guayaquil MSP Global Storytelling Tool Here](https://storytelling.mspglobal2030.org/spac/?lang=en)**

[MSPglobal](https://www.mspglobal2030.org/msp-global/) is a joint initiative by UNESCO’s Intergovernmental Oceanographic Commission (IOC-UNESCO) and the European Commission’s Directorate-General for Maritime Affairs and Fisheries (DG MARE) to develop and implement international guidelines on Marine/Maritime Spatial Planning. MSP is an important tool to foster integrated planning and management practices to protect and restore marine and coastal ecosystems, strengthen resilience, and promote a healthy and productive ocean. MSP Global facilitates the active and effective participation of policymakers, scientists, citizens, and other stakeholders to improve governance and achieve an ecosystem-based approach in support of the blue economy. Within this framework, we at Randbee Consultants developed multilingual storytelling tools based on varying factors within the Western Mediterranean (offered in Arabic, amongst other languages) and Guayaquil in Ecuador (offered in Spanish, amongst others). We presented the data and information in a simplified and interactive way with the goal of raising awareness about the need for dialogue and cooperation for the development of a Sustainable Blue Economy in both regions. We provided an impactful solution by delivering effective storytelling products that reached a broad audience due to their multilingual nature and produced compelling insights that can ultimately influence decisions for the better.

**2. Tsunami Ready Viewer**

![image3.png](https://randbee.com/strapi/uploads/image3_0e399840ed.png)

**[Check out the Tsunami Ready Tool here](https://tsunamireadyviewer.ioc-tsunami.org/)**

Tsunami Ready is an international performance-based community [Recognition Programme](https://tsunami.ioc.unesco.org/en/pacific?option=com_content&view=category&id=2234&Itemid=2758) under the UNESCO Intergovernmental Oceanographic Commission (IOC) and is facilitated by its Tsunami information Centres. Tsunami Ready consists of key actions that help to reduce tsunami-related risks to individuals and communities to ensure they are prepared in the event of a tsunami. We led in the development of The Tsunami Ready Communities web-based interactive tool, which provides comprehensive access to supporting maps and other resources and aims to increase the visibility of the global Tsunami Ready Communities which have been recognised or are being prepared under the UNESCO-IOC led programme. It is also a critical tool for achieving key global targets for the United Nations Decade of Ocean Science for Sustainable Development (2021-2030) being led by UNESCO-IOC. We were able to demonstrate our talents using web-based map tools in order to create an engaging and informative [tool](https://tsunamireadyviewer.ioc-tsunami.org/) that bridges the gap between data and action, reducing the risk to people in critical danger by giving them time to prepare for an approaching tsunami. Furthermore, a geocoding tool has been made available, which uses an Excel file to georeference the latest version of the communities in the Programme automatically, allowing for an easy (and non-expert) update of the communities displayed in the Viewer.  We at Randbee strongly believe that the true value of data is realised when it is translated into meaningful insights through effective communication, enabling us to provide impactful solutions, and in this case, potentially save lives. 

### Conclusion

Data storytelling presents an exciting frontier where technology, creativity, and data converge to revolutionise how we communicate insights and make decisions. We believe that the world of data visualisation will evolve into a more simplistic space as the need to understand complex data increases. The demand for visualisations that relinquish any complexities will therefore increase, with a focus on delivering core messages as effectively and succinctly as possible. Through our technical ability and experience, we are able to combine complex data with simple yet effective visuals, and a memorable narrative to create a clear, cohesive, and persuasive message that can be easily grasped by a broad audience. 

So, if you have data that needs to be transformed into a story, get in touch [here](https://randbee.com/contact), and let’s chat about how we can help to develop a compelling storytelling tool that not only informs but inspires and improves decision-making to drive change. 

Check out our other [projects](https://randbee.com/projects) and follow us on our [socials](https://x.com/RandbeeCo) to see how we else we’ve been transforming the data world!




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It’s widely believed that data is one of the most powerful mechanisms for telling stories. However, how can you create a story with numbers I hear you ask? The key is to weave that data into a compelling narrative that will resonate with individuals, just like any other good story you’ve read before. 

Data storytelling: The art of crafting a compelling story from data

The progression of AI is moving so fast that you can’t afford to take your finger off the pulse. With complex data sources, how can multiple business sectors take reliable, actionable insights to inform strategic and operational decisions to maintain a competitive edge?

Enter Large Language Models (LLMs), which are advanced AI systems designed to understand and generate human-like text. They can enhance productivity, efficiency, and innovation across multiple industries from finance to environmental, and are revolutionizing the way we interact with technology and data analysis. Unfortunately, LLMs also come with various limitations, particularly in generating false information (hallucinations), citing sources and limited scope of knowledge. Furthermore, the stochastic nature of responses makes integrating an LLM into a business process challenging, unless it is implemented into a robust design process. This is because the outputs can vary even with the same input which is problematic for tasks that require consistency and reliability. 

In this blog post, we will explore how Randbee Consultants integrates Retrieval-Augmented Generation (RAG) with data scraping to overcome these limitations and provide valuable insights for diverse industries. 

### LLMs: Strengths and Shortcomings

**Advantages:**

- **Complexity:** LLMs excel at interpreting context, detecting sentiment, and understanding idiomatic expressions. This helps to answer complex questions and aids more intuitive human-computer interactions. 

- **Quality:** LLMs can generate high-quality text, making them useful for tasks such as language translation, and even code generation.

**Limitations:**

- **Insufficient parsing:** LLMs can struggle with parsing unstructured formats like complex PDF’s which often contain a mix of text, images, tables and other elements.

- **Hallucination in LLMs:** refers to the generation of incorrect or nonsensical information that appears plausible. This happens when LLM fills in gaps often due to training bias or inaccuracies, model complexities, or inability to process new or technical terms. 

- **Lack of domain-specific knowledge:**  LLMs often struggle to generate accurate responses in specialised fields (such as in the environmental or financial industries) due to the fact they are often trained with generic data on the internet. 

### Introducing RAG: A Complementary Solution

RAG is a technique used in artificial intelligence to enhance the performance of LLMs by integrating external knowledge sources to ensure outputs are grounded in verified data. The system first retrieves relevant information from external sources, based on the user’s query. This retrieved information is then used to augment the input to the language model which generates a more accurate response using both training data and the newly retrieved information.  

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*LLMs can sometimes fall short when faced with the need for precise, domain-specific knowledge. RAG is a powerful technique designed to bridge the divide between this generalized knowledge and specialised information.*

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### Why RAG Works Across Multiple Sectors

- **Enhanced Accuracy and Relevance:** Industries such as healthcare, finance and the environmental sector all require accurate and up-to-date information. RAG integrates external knowledge sources to ensure responses are contextually relevant and current. This also improves decision-making. 

- **Efficiency and Innovation:** RAG enhances efficiency and innovation by automating the retrieval and generation of information. This is especially useful in technology and engineering industries where solving complex challenges and integrating large amounts of data is key.

- **Transparency and Trust:** RAG systems can provide information sources, which in turn enhances credibility and trust. Transparency is essential in industries such as journalism and academia, where it is of paramount importance to provide reliable information. 

### The Randbee Approach: Versatility in AI Solutions

At Randbee Consultants, we are masters of data manipulation, and our ability to leverage RAG and automated data scraping allows us to create flexible, robust solutions that meet diverse sector needs.

There are three fundamental steps involved to deliver insightful data-driven solutions using RAG:

1. **Data Collection:** We scrape and preprocess diverse data types (e.g: PDFs, databases, reports) to ensure efficient retrieval and vectorization. 

2. **Insight Generation:** We leverage the integration of RAG combined with the strengths of LLMs and retrieval systems to generate responses which are grounded in real-time and relevant information.

3. **User-Friendly Access:** We deliver insights through accessible interfaces tailored to non-technical users. For example, we use simple language, clear visuals, and interactive elements which can make the data insights easier to understand and ensure that the information is relevant and actionable. 

### Real-World Applications: Harnessing RAG to Inform Climate Action Plans

**The Challenge:** Creating climate action plans often involve analysing large amounts of data depending on the scope and complexity of the plan, which can be extremely time- consuming, involve a huge amount of manpower and costs, and can often lead to erroneous results. 

**The Solution:** At Randbee Consultants, using our extensive experience and in-depth knowledge of RAG, we can extract insights from sustainability reports and policy documents to successfully inform climate action plans. Our RAG-based platform scrapes data from environmental PDFs amongst other documents, summarizing key points and extracting relevant information, presenting actionable insights to streamline sustainable decision-making. In order to generate these valuable insights, we possess high-impact tools such as a powerful parser for document analysis, and advanced RAG using Plan and Execute Agent. Plan Agent is responsible for creating a structured plan or strategy for information retrieval and generation, and Execute Agent carries out the retrieval and generation tasks once the plan is in place. Our method using both Agents is an innovative approach that greatly enhances the capabilities of traditional RAG systems. 

**The Outcome:** We are able to significantly reduce the time spent on manual data collection by automating the retrieval and processing of relevant information using RAG. Our extensive knowledge and specialised tools allow us to create dynamic tailored insights to empower informed decisions, supporting the creation of an impactful and transformative climate action plan.  Furthermore, as RAG can quickly integrate new information, we can facilitate in updating and adapting any document. 

### Benefits of Randbees Powerful Technology and Expertise

**Efficiency:** Our expertise in automating data collection and preprocessing ensures that less time is spent manually searching for data, allowing users to understand and act upon complex data in a timely manner. 

**Precision:** Our ability to leverage RAG ensures that decision-makers use information based on accurate and reliable data, as RAG uses verified external sources to ground its content. This also reduces the risk of misinformation, which is essential when developing important documentation and reports.

**Flexibility:** Harnessing our powerful technology and applying our long-standing expertise combining RAG and LLMs, we are able to enhance decision-making across a wide range of industries such as environmental, legal, financial, and healthcare.  Furthermore, our work facilitates improved communication with stakeholders, including the public, NGOs, and government officials due to our ability to produce clear and concise summaries of complex data. 

**Accessibility:** In addition to generating accessible interfaces tailored to non-technical users, we are able to leverage RAG to assist in translating and summarizing documents in multiple languages, which makes information accessible to a broader audience. This in turn can promote collaboration and information sharing on a global scale. 

> "The collaboration with Randbee Consultants was a transformative process from day one. They created a comprehensive plan and helped to initiate our AI development, using powerful modern technologies. The benefits to our business have been outstanding, saving us an enormous amount of time and allowing us to improve the efficiency and precision of our data management" - **University in Spain**

### Future Vision: Scaling AI Solutions for Broader Impact

The world of AI solutions is rapidly evolving to improve the accuracy and versatility of these systems, with numerous groundbreaking innovations emerging. For example, we believe that enhancing the scalability of RAG will be essential with the ever-increasing volumes of data, and the development of more efficient algorithms and infrastructure will support this progression. Furthermore, innovations are focusing on making RAG-based systems more adaptable to emerging sectors such as specialized medical knowledge and language nuances. Finally, being environmentally aware is a passion of ours, and AI can offer deeper insights into sustainability practices, helping organizations to be socially responsible and make decisions based on their environmental impact. 

These ongoing innovations are driving the next wave of advancements in RAG, and we at Randbee Consultants believe that a data-driven future involves supporting sustainable, informed decision-making across all industries and sectors.

### Conclusion

It is evident that LLMs alone are not sufficient for extracting actionable insights from complex datasets. However, combining LLMs with retrieval techniques such as RAG creates a powerful tool that has led to significant improvements in generating highly accurate and contextually relevant information, allowing multiple sectors to make informed decisions based on reliable data. 

Our technology plays a crucial role in developing intelligent, context-aware systems that push the boundaries of what language models can achieve. If you want to learn more about how Randbee Consultants is leveraging AI to drive innovation across industries from environmental management to corporate strategy, click [here](https://randbee.com/contact) to get in touch. Make sure you follow us on our social media [platforms](https://www.linkedin.com/company/randbee) to keep up to date with our [latest](https://randbee.com/projects) projects!

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The progression of AI is moving so fast that you can’t afford to take your finger off the pulse. With complex data sources, how can multiple business sectors take reliable, actionable insights to inform strategic and operational decisions to maintain a competitive edge?

Harnessing AI: Combining LLMs with RAG to provide valuable insights to diverse industries

Last month, we were excited to host the latest Generative AI Seville Meetup at our Randbee Consultants office in Seville. This time round, Jose from Randbee presented; Jose is an industrial engineer and has worked in the field of data simulations for many years. We are privileged to have him work alongside us in our office as a Data Scientist. On the night of the Meetup, Jose shared his knowledge with us on LLMs (Large Language Models) and the design of AI agents (Plan and Execute) with LangGraph and Pydantic frameworks.

In this blog post we will explore Agentic AI’s core concepts, how to integrate it, and the challenges and solutions associated with it. We will then look at how to implement an Agentic system with a LangGraph Framework, showcasing a demo with a Plan and Execute architecture.

### What is Agentic AI?

**"Agentic": Having agency; the ability to make independent decisions in pursuit of a goal without constant external direction or intervention.**

We started to explain how Agentic AI represents a significant leap in artificial intelligence, moving beyond traditional automation and generative AI. It refers to a system based on different AI/LLMs that can function with autonomy to achieve a certain goal. Essentially, AI systems that can operate independently without the need for human intervention. This is contrary to standard AI which follows predefined workflows or responds to specific queries. 

### Agentic AI: The core concepts

We then went on to explain some of the core concepts of agentic AI and how it can be implemented. Some of these core concepts are outlined below:

**Autonomy:** Agentic AI can independently make decisions, plan actions, and execute tasks without needing human guidance. 

**Problem Solving:** These systems hold advanced reasoning capabilities which allow them to analyse complex situations, break down problems into smaller steps, and formulate strategies to achieve goals. 

**Goal Orientation:** To ensure successful outcomes, Agentic AI works towards predesigned objectives constantly evaluating progress and adjusting its actions.

**Context Awareness:** It can make more informed and effective decisions by adapting to its environment and incorporating context. 

**Iterative Improvement:** Agentic AI can refine its methods through feedback, learning from its experiences to enhance performance over time. 

**Integration with Tools:** Agentic AI can leverage external tools, API and databases, functioning as a mediator between systems to complete multi-faceted objectives.

### How to implement Agentic AI

We explained that implementing Agentic AI involves multiple key steps to ensure the system is autonomous, goal-orientated, and effective. Jose stressed that the first and most important step is to define your goals and outline methods of data collection. He advised the audience to start by clearly outlining the objectives that the AI system should achieve and preprocess data from diverse sources, ensuring it is clean, relevant, and comprehensive. Step number 2 involves choosing the right algorithms by selecting those that support autonomy, reasoning and decision-making. Jose then highlighted step number 3, which is to create a robust architecture that integrates memory, reasoning, and action capabilities. This includes designing feedback loops for continuous learning and improvement.

Step number 4 involves equipping the AI with the ability to interact with external tools, APIs, and databases to perform complex tasks and access real-time information. Finally, step number 5 is to define ethical boundaries and ensure the AI aligns with societal norms, legal requirements, and organisational values. This involves deploying the AI system in a controlled environment and continuously monitoring its performance, where adjustments can be made as needed.


### Challenges with agentic AI and how to avoid them

While agentic AI is set to be a groundbreaking system, we explained that its autonomous and decision-making capabilities can lead to a range of challenges and concerns. However, these can largely be mitigated when thoughtful design and robust safeguards are implemented. Jose outlined some key problems associated with agentic AI, and luckily for us, how to avoid them.

#### Loss of Control

- **Challenge:** Agentic AI operates with a high level of autonomy, acting in ways that are unanticipated or potentially difficult for humans to influence.

- **Solution:** Implement human-in-the-loop systems where humans review critical decisions. Also, ensure control and override capabilities remain intact by using rigorous fail-safes and monitoring mechanisms.

#### Ethical Dilemmas

- **Challenge:** It’s complex to align agentic AI’s actions with human values. Ethically questionable decisions can stem from unintended biases or conflicting objectives. 

- **Solution:** Incorporate ethics into AI design through value alignment, bias detection, and fairness algorithms. Furthermore, be sure to establish transparent and explainable AI systems that justify their decisions.

#### Security Risks 

- **Challenge:** Autonomous systems can be vulnerable to cyberattacks or manipulation.

- **Solution:** Use AI monitoring systems to detect and counter malicious activity. Consider strengthening cybersecurity protocols, encrypting data and conducting regular vulnerability assessments.

#### Environmental Impact

- **Challenge:** Advanced AI systems can have a significant environmental footprint due to energy consumption.

- **Solution:** Use green data centres, optimise AI models for efficiency and prioritise sustainable practices in AI development.

We highlighted that addressing these issues requires a robust ethical framework, transparent development processes, and strict regulations to ensure that agentic AI is beneficial and safe.  Jose stressed that in order to achieve this a collaborative effort between developers, regulators and society is key.

### How to implement an Agentic System with the LangGraph framework

We explained that LangGraph is based on a state graph structure and is a framework that allows us to design and manage complex agentic systems. It also provides tools and libraries to build, deploy, and optimise workflows for LLMs. Jose explained that typically, agents use LLMs as general-purpose problem-solvers, connecting them with external resources to answer questions or accomplish tasks through repeated thought, act, observation loop. Whilst this is okay for simple tasks, it does also have some drawbacks. One way to overcome these shortcomings is through implementing a Plan and Execute agent architecture which adds an explicit planning step and multi-tool selection to demonstrate autonomous decision making.

This involves creating a system where the agent first develops a comprehensive plan and then executes it step by step through a planning phase (where the agent uses an LLM to analyse the task and break it into smaller, manageable sub-tasks), execution phase (where the agent performs each sub-task sequentially or in parallel), and finally the replanning phase (where the agent reevaluates the situation and adjusts its plan accordingly if something goes wrong).

We briefly described how to integrate an Agentic AI system with a LangGraph framework, outlined below:

1. **Install LangGraph and Define Workflow:** Start by installing the framework and its dependencies. After this, break the task into smaller steps and use LangGraph's ***TaskNode*** and ***Workflow*** components to structure the flow of these steps.

2. **Create Agents and Integrate Tools:** Assign agents for specific tasks like planning and execution within your workflow. Then incorporate LLMSs or domain-specific tools to perform specialised tasks (such as data retrieval).

3. **Run and Test:** Execute the workflow, monitor real-time performance with LangGraph's streaming support, and optimise based on the results.

### LangGraph Demo: A Plan and Execute Architecture

In this demo, you will see the above steps put into action as we explored the capabilities of a Plan and Execute system, developed using a LangGraph and Pydantic Framework. As part of Randbee’s demo, Jose explained that by integrating three different tools (based on weather prediction), we can see how the system can effectively choose the most appropriate tool based on the user query, demonstrating autonomy.

**1. Tools**

In Randbee’s demo, there were three different types of tools for the system to choose from:

- A self-defined tool with weather descriptions in South America (based on three capital cities: Buenos Aires; Santiago de Chile; and Lima).
- A vector database-based tool with weather descriptions in North America (based on three capital cities: Boston; Phoenix; and Sacramento).
- A web search-based tool for the weather in the rest of the world (i.e. excluding North and South America).

The system must be able to choose the most appropriate tool based on the part of the world that the user is requesting weather for.

**2. Prompt Templates**

A prompt template provides a framework to help generate a specific kind of response. To effectively guide the system on using the three tools, different templates must be used on the Plan and Execute architecture. For example, for the executor phase:

- Use the **get_ weather_south_america** tool to retrieve weather data for South American capital cities.
- Use the **get_weather_north_america** tool to retrieve weather data for North American capitals.
- If the city is not in North or South America, use the **tavily_search** tool to retrieve weather information.
- If the weather data is not found, return the following message: **"Weather data for this city is not available."**
- Provide clear and concise answers, ensuring that each response contains the name of the city and the temperature and humidity information if found.
- Always indicate if the information is not available for a requested city.

**3. Pydantic and Structured outputs**

We explained that for the system to be consistent between the different phases (planning, execute and replanning) the information needs to be structured between them, and this is when the Pydantic framework is useful. Use the **('PlanExecute')**, **('Plan')**, **('Response')**, and **('Act')** classes to structure the data.

**4. Plan and Execute Logic**

For the system to work correctly, the logic of the transitions between the phases (plan, execute and replan) must be defined using the [**workflow_logic.py**](https://github.com/Randbee/meetup_langgraph/blob/main/src/workflow_logic.py).

**5. Plan and Execute Workflow**

Finally, once all the elements have been ensembled, the system can be queried. In this section, the phases of the Plan and Execute System (plan, execute, replan) need to be compiled with all the definitions (tools, prompt templates...) using commands such as **```"input"```**, **```"plan"```**, **```"past_steps"```** and **```"response"```**. Then the system is ready to accept the user queries and deliver the response.

![workflow.png](https://randbee.com/strapi/uploads/workflow_6c928da980.png)

All the code and slides are available in this **[repository](https://github.com/Randbee/meetup_langgraph)**.


### Conclusion

Agentic AI is poised to reshape how we interact with technology going forward, and we are proud that Randbee Consultants is at the forefront of these developments. This blog post has taught us that LangGraph provides the essential framework for building and managing AI workflows and agentic systems. It ensures robust task management by supporting the implementation of both the planning and execution phases.  We also learned that using a Plan and Execute architecture helps to break down complex queries into smaller steps, and therefore the agent can achieve higher task completion rates and better-quality results. Finally, by evaluating the outcomes of each step, the agent can adjust its plan as needed, demonstrating autonomy of decisions.

As always, we are grateful to those who participated in this Meetup event, and we would like to thank everyone who contributed to the dynamic and thought-provoking discussions on the night. If you’re keen to find out more about any of the information in this blog post get in touch with Randbee Consultants [here](https://randbee.com/contact). Also check out some of our other [projects](https://randbee.com/projects) to learn more about the world of Data Science, AI and the integral role sustainability plays in underpinning Randbee’s mission to make the world a better place.

Follow us on our [socials](https://www.linkedin.com/company/randbee) to see our latest endeavours and keep a lookout for our next Meetup event!





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Last month we were thrilled to host our latest Meetup event here at our Randbee Consultants office in Seville.