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AI Transformation Services

Our UK-based transformation consultants and analysts specialise in defining requirements and solutions for intelligent process automation, enhancing efficiency and driving positive change for our clients of all sizes.

Whether you’re still exploring your options or have a clear path in place, we support the analysis and implementation of cutting-edge digital solutions.

We scope small incremental changes or full programmes – integrating new technologies such as AI and process automation to ensure lasting impact.

We partner with our clients to ensure technology delivers real value:

  • Automation and AI are implemented thoughtfully, only where they truly enhance outcomes
  • Advanced tools are used to empower, not replace, human workers
  • We support workforce reskilling to help teams adapt and thrive alongside new technologies

Explore our services and discover how we can help add value to your business.

News and Articles

Explore our collection of insightful business transformation and technology news articles

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Knowledge Cards

These pages give overviews of technical terms that you may encounter in transformation programmes, along with real world examples and FAQ

TOGAF Implementation

TOGAF Implementation refers to the process of applying the TOGAF framework within an organisation to guide the design, planning, and management of its enterprise architecture. It involves using TOGAF's methods, tools, and standards to align business goals with IT strategy, ensuring that technology supports organisational needs. A successful implementation helps to structure processes, improve communication, and manage change more effectively across departments.

Data Mesh Implementation

Data Mesh implementation is the process of setting up a data management approach where data is handled as a product by individual teams. Instead of a central data team managing everything, each team is responsible for the quality, ownership, and accessibility of their own data. This approach helps large organisations scale their data operations by distributing responsibilities and making data easier to use across departments.

Named Recognition

Named recognition refers to the process of identifying and classifying proper names, such as people, organisations, or places, within a body of text. This task is often handled by computer systems that scan documents to pick out and categorise these names. It is a foundational technique in natural language processing used to make sense of unstructured information.

Data Compliance Metrics

Data compliance metrics are measurements used to track how well an organisation follows rules and regulations for handling data. These metrics help ensure that sensitive information is collected, stored, and processed in ways that meet legal and industry standards. Organisations use these metrics to identify gaps, reduce risks, and prove their data practices are compliant during audits or reviews.

Ensemble Diversity Metrics

Ensemble diversity metrics are measures used to determine how different the individual models in an ensemble are from each other. In machine learning, ensembles combine multiple models to improve accuracy and robustness. High diversity among models often leads to better overall performance, as errors made by one model can be corrected by others. These metrics help assess whether the ensemble benefits from a good mix of independent predictions, rather than all models making similar mistakes.

AI for Particle Physics

AI for Particle Physics refers to the use of artificial intelligence techniques, such as machine learning and deep learning, to help scientists analyse and interpret data from experiments in particle physics. These experiments produce vast amounts of complex data that are difficult and time-consuming for humans to process manually. By applying AI, researchers can identify patterns, classify events, and make predictions more efficiently, leading to faster and more accurate discoveries.

Token Utility Frameworks

A token utility framework is a structured way to define how a digital token can be used within a blockchain-based system. It outlines the specific roles, rights, and functions that the token provides to its holders, such as access to services, voting on decisions, or earning rewards. By setting clear rules and purposes, these frameworks help ensure that a token has real value and practical use within its ecosystem.

Encrypted Feature Processing

Encrypted feature processing is a technique used to analyse and work with data that has been encrypted for privacy or security reasons. Instead of decrypting the data, computations and analysis are performed directly on the encrypted values. This protects sensitive information while still allowing useful insights or machine learning models to be developed. It is particularly important in fields where personal or confidential data must be protected, such as healthcare or finance.

Transformation Heatmaps

Transformation heatmaps are visual tools that display how data points change or move after a transformation, such as scaling, rotating, or shifting. They use colours to show areas of higher or lower concentration, making it easy to spot patterns or differences before and after changes. These heatmaps help users quickly understand the effects of transformations in data, images, or other visual content.

Discretionary Access Control (DAC)

Discretionary Access Control, or DAC, is a method for managing access to resources like files or folders. It allows the owner of a resource to decide who can view or edit it. This approach gives users flexibility to share or restrict access based on their own preferences. DAC is commonly used in many operating systems and applications to control permissions. The system relies on the owner's decisions rather than rules set by administrators.