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Transforming Public Sector with AI: Enhancing |

Leading AI-driven advancements for enhanced security, efficiency, and strategic excellence in the public sector.

Introducing Applied Data Science Partners

Applied Data Science Partners (ADSP) is a London-based consultancy founded in 2016, specialising in developing transformative artificial intelligence (AI) solutions that revolutionise the way organisations operate.

We work across both private and public sectors, tackling complex challenges in critical areas such as defence, aerospace, and the broader public domain. By focusing on innovation, collaboration, and operational excellence, we empower organisations to make smarter, data-driven decisions while staying ahead in an ever-evolving digital landscape.

Trusted by Leading Public Sector Entities

ADSP partners with renowned public sector organisations, including the UK Ministry of Defence (MoD), the Greater London Authority, LocalGov Associations, and the UK Parliament, to deliver impactful AI-driven transformations that enhance efficiency and improve public services. Notably, we collaborate with the European Space Agency (ESA), using cutting-edge AI methodologies to optimise satellite design and drive technological innovation.
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These trusted partnerships highlight our expertise in delivering actionable, bespoke AI solutions that address the unique challenges of public sector organisations, improve outcomes, and foster meaningful progress.

Empowering Defence and Public Services with Bespoke AI

Cybersecurity

ADSP uses advanced reinforcement learning to train AI systems for defending networks against diverse cyber threats. By simulating various attack scenarios, our AI systems continuously improve defensive strategies, enabling real-time threat detection and mitigation, ensuring robust network security for defence operations.

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    Multi-Agent Reinforcement Learning

    Our Multi-Agent Reinforcement Learning (MARL) work develops collaborative AI agents to optimise defence operations through coordination, scenario analysis, and adaptive learning, particularly effective in large-scale simulations and strategic planning.

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      War Gaming

      ADSP's war gaming projects simulate potential military scenarios to aid strategic planning and decision-making. These AI-driven simulations help defence planners understand and predict outcomes, evaluate tactics, and develop robust defence strategies, ensuring preparedness and tactical advantage.

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        Our Frameworks and Trusted Partners

        G- Cloud
        Digital outcomes and specialists
        Astrid
        Serapis
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        ACE
        HealthTrust Europe

        ADSP and the MoD

        Over the past few years, ADSP has successfully delivered several AI projects for the MOD, playing a pivotal role in advancing AI and ML techniques in cyber defence. Our key contributions include:

        LLM Agents for Cyber Defence: A Zero-Shot Approach

        Task 37: Investigated using LLMs as defence agents to reduce reliance on traditional training methods, demonstrating a 90%-win rate on specific environments.

        • Blue squareTask 32: Aims to review the evolving LLM landscape, focusing on reducing latency and expanding memory options to enhance agent performance.
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        A Generalist RL Agent for Cyber Defence

        Task 18: Demonstrated the creation of a single, versatile agent capable of effectively operating across multiple cyber environments.

        • Blue squareTask 40: Created adaptors to streamline RL projects and demonstrate the potential to integrate and analyse various RL models efficiently.
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        Minimum Viable Product (MVP) Agent Integration

        Task 8: Implemented the first integration of a pioneer agent into complex environments, leading to the demonstration of an ML cyber defender outperforming a rules-based agent developed with a human analyst.

        • Blue squareTask 19: Showcased that RL could learn to handle more complex simulation environments, achieving a milestone in addressing the Sim-to-Real challenge.
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        Decoy Agents: A Generative Approach to Deception

        Task 36: Explored the efficacy of using Large Language Models (LLMs) to create realistic decoys to deceive attackers and deflect from intended targets.

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          Talk-To-Your-Components: Human Programming Interfaces

          Task 38: Demonstrated LLMs equipped with retrieval augmented generation (RAG) to interpret complex cybersecurity data into human-readable output.

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            Probabilistic Graphical Models for Agent Planning

            Task 49: Implements a probabilistic graphical model to allow the agent to select actions with a higher likelihood of success, anticipating outcomes.

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              Data Efficient Reinforcement Learning

              Task 17: Proved the ability for the Self-Predictive Representations (SPR) technique to generalise better to unseen tasks more effectively than traditional RL techniques.

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                Defence Environment Simulations

                Task 28: Enabled testing and validation of defence agents in complex cyber environments, enhancing adaptability and effectiveness.

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                  Extending Reinforcement Learning Capabilities

                  Task 50: Focuses on extending and developing proof-of-concept agent and environment adaptors, enabling other groups to utilise the adaptor functionality.

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                    Secure by Design

                    Quality and Security Certifications

                    Building solutions is serious business in the modern day. That's why we're proud to be certified by the British Standards Institute (BSI) in both Information Security (ISO 27001) and Quality Management (ISO 9001).
                    Achieving ISO 9001 underscores our commitment to delivering high-quality AI solutions with consistent excellence across all projects. ISO 27001 certification demonstrates our dedication to maintaining the highest standards of information security, ensuring the protection of client data.
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                    Thought Leadership

                    Why choose ADSP for Data Science Consulting?

                    Thought Leadership

                    At ADSP, we offer a deep understanding of generative AI models, from the technical details of their architectures to the practical applications and customisation strategies that drive real-world value and impact. We are uniquely placed to guide and support you in harnessing the power of generative AI, empowering your organisation to thrive in an increasingly competitive landscape. ADSP is co-founded by David Foster, author of the bestselling O'Reilly textbook Generative Deep Learning.

                    David Foster Headshot

                    David Foster

                    Founding Partner, ADSP

                    Generative Deep Learning

                    Frequently Asked Questions

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