Data & Artificial Intelligence

In brief: Design and implementation of trusted data pipelines, integration layers and governed data stores that make operational data usable across analytics, automation and AI.

In brief: Dashboards, performance models and analytical applications that convert governed data into operational and executive decisions.

In brief: Machine-learning solutions that forecast, classify, detect anomalies, recommend actions or optimize decisions using validated data and measurable performance criteria.

In brief: Enterprise generative-AI applications for content, search, summarization, drafting and knowledge assistance, engineered with retrieval, evaluation and human oversight.

In brief: Task-oriented agents that reason over approved knowledge, use governed tools and coordinate multi-step business workflows under explicit permissions and oversight.

In brief: Capture, classify, extract, validate and route information from forms, invoices, contracts, claims and operational documents.

In brief: Vision and speech systems for inspection, recognition, transcription, monitoring and edge-based inference in operational environments.

In brief: Governance, lifecycle controls and operational tooling for responsibly deploying, monitoring and retiring AI models and AI-enabled applications.

In brief: Independent, continuous quality assurance for software and AI systems: test strategy, functional and regression coverage, automation, performance and security verification, delivered as a managed service with evidence th

In brief: Machine-learning model training run as a managed engagement: task framing, training-data preparation, supervised runs with tracked experiments, evaluation against an agreed baseline, and handover of the trained model wit

In brief: Independent testing of machine-learning models before and after deployment: accuracy against holdout data, robustness under drift and adversarial input, bias and fairness measurement, and behavioural verification of gene

In brief: The data groundwork every model and dashboard depends on, run as a managed service: locating and acquiring the right data, lawful-basis checks, de-duplication, standardisation, labelling coordination and quality measurem