For over 60 years Allan Webb Ltd (“AWL”) has been a leading supplier of data intelligence solutions and services to the UK MoD and other government departments, as well industry and commercial clients throughout UK and Europe.  Our data solutions and capabilities extend across multiple industries and sectors, including aerospace, defence, maritime, manufacturing, rail, power generation and utilities.

Over the last few decades data has evolved from being well structured and typically housed in single databases and repositories, to the complex “big data” we see all around us.  In particular, data is no longer neatly packaged into single silos ready for traditional analysis and analytics.  Instead, real-world data is complex, comes in different varieties and formats (pictures, documents, video, images, transactional data, time series data, sensor data, maps etc), suffers from serious data quality issues (often incomplete, inaccurate out-of-date and even biased) and is regularly spread across multiple systems, databases and silos, both on-premises and cloud based.

At AWL we have been evolving and adapting to meet these new data challenges head-on.  Our Data Science and Data Intelligence team are leading, researching and developing cutting-edge data solutions and capabilities, leveraging the latest advances in data management, artificial intelligence, machine learning, and data intelligence.

We believe that as data volumes continue to grow exponentially, as data complexity increases and with new data varieties still emerging, it is imperative that we deliver “data led” solutions and services, rather than being “data driven” or “data pushed”.


Artificial Intelligence and Machine Learning

Whether it is standard supervised (regression, Support Vector Machines, decision trees and random forests) or unsupervised (clustering, dimensionality reduction, association rule mining) machine learning methods, or the latest advances in deep learning and natural language processing, data and AI are at the heart of our products and services.

As a trusted partner to the UK MoD and other key defence industry partners, we are working with them on a range of AI and data projects.

For example, in conjunction with the MoD we recently developed an AI model to predict obsolescence risk of equipment aboard Royal Navy vessels.  The outcome of our solution was an increase in accuracy of 75%, allowing the client to better predict the obsolescence status of key parts aboard Navy vessels.

In addition, last year we commenced an R&D phase to apply advanced computer vision techniques to identify parts and items of machinery from technical drawings with the aim of developing a solution capable of assisting with NATO codification tasks, as well as extracting information from Illustrated Parts Catalogues.


Graph Analytics and Capabilities

At AWL we are partnering with some of the world’s leading graph database and graph visualisation companies to develop new cutting-edge solutions for a range of use-cases.

For instance, we are currently developing a graph based system for Master Data Management, working across disparate silos to reveal the relationships hidden in master data as well as deliver single sources of truth.

We are also using graphs to understand complex Bills of Materials, to understand the dependencies between components and equipment across military assets, as well as understanding how spares and parts can be sourced in complex supply chain networks. 

We are also researching how Natural Language Processing (“NLP”) techniques, OWL based ontologies and Resource Description Framework (“RDF”) graphs can be used to build insights between entities and relationships from technical and other documents.

Data Analytics and Intelligence

Our Data Intelligence team have the skills and experience to leverage tools such as Tableau, Microsoft’s Power BI, as well as Python and R to generate high-impact dashboards and visualisations to deliver data-led decision making. For example, for the MoD we have been developing an AI solution with a fully-interactive Python dashboard to assist with the automatic classification of master equipment items aboard Royal Navy vessels.  Our solution has resulted in a multiple-fold increase in accuracy of correctly identified parts, as well as a significantly reducing time spent manually identifying parts.

We have also developed our DiamondWebbTM solution, which is currently deployed across various legacy and digital navy platforms, from the new Queen Elizabeth Class to Astute and Vanguard Class vessels. Our solution takes source data from over 15 MoD inventory systems and maps it to a single source of truth to provide a virtual configuration view of an asset, to identify gaps and conflicts in data.  In a recent application of our solution, we were able to identify the relevant data for over 100,000 items, saving our client’s time, cost and effort.

Data Analytics and Intelligence

Explainable AI

At AWL we understand that many AI and ML models are “black-box” in nature, making predictions that are difficult to interpret or understand.  Whilst this is particularly true of so-called deep learning models, it also applies to many of the standard machine learning models including Support Vector Machines and random forests. 

We believe Explainable AI (“XAI”) is crucial to providing transparency and understanding of a model’s behaviour and predictions, key ingredients to effective and confident decision making.

We have developed an XAI framework, including utilising model agnostic explainability methods such as SHAP (SHapley Additive exPlanations) and LIME (Local Interpretable Model-agnostic Explanations) to deliver best-in-class AI models whose predictions are interpretable and understandable.

If you would like to know more about why an XAI framework is crucial when developing AI solutions, contact


Research and Thought Leadership

AWL collaborates and works in partnership with domain specialists in the UK MoD, key industry partners and with leading UK academics.

For example, with the University of Bath we will be sponsoring a PhD student to research how graph models and graph databases behave when complex temporal phenomena are modelled. We are developing the next generation of predictive graph models that allow for spatial as well as temporal dimensions. If you would like to know more about our graph research with the University of Bath, please contact


Our extensive portfolio of training courses, from obsolescence risk management to systems engineering across the life-cycle, are highly sought after, with many courses accredited to The Chartered Institute of Logistics and Transport for Continuous Professional Development.  Our courses encourage individuals to develop ideas and inspire positive change in thoughts, driving thought leadership.


Security & Quality


Quality is at the heart of everything we do. Our ISO 9001 certified operational procedures are constantly reviewed and updated to ensure that our quality is second to none. 

Combined with our ISO 27001 and Cyber Essentials Plus certifications, AWL is able to demonstrate full commitment to delivering services on time and right first time whilst ensuring your data is always protected.




ISO 14001ISO 27001ISO 9001Cyber EssentialsADS SC21 Award
Armed Forces Covenant

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