Evidence
Trace conclusions to source documents, data and the discrepancies that matter. Design for provenance, verification and explicit uncertainty—not unsupported confidence.
Specialist capabilities
The engineering behind decision-grade AI.
ARVEC connects AI architecture, evidence extraction, semantic knowledge, enterprise operating capability and risk analytics around one test: can the resulting decision be traced, understood, reviewed and operated responsibly?
Three foundations, six areas of work.
Evidence, meaning and control are the lens we use to organise the work. They are not the boundary of it: most engagements draw on more than one area, and each area below stands on its own.
Meaning
Represent the entities, relationships and domain rules that determine what information means within a business process.
Control
Define limits, accountability, approval paths and human oversight so AI-assisted decisions fit the way regulated organisations actually operate.
Areas of expertise
What we design and engineer.
E01
AI Architecture & Engineering
Design production-oriented AI systems where evidence flows, model behaviour, integration boundaries, evaluation, observability and accountable operation are considered together.
Sample outputs
Reference architecture · Data and knowledge flow · Control points · Evaluation plan · Implementation design
E02
Document & Knowledge Intelligence
Extract, reconcile and verify information across complex documents and knowledge sources, with traceable citations, discrepancy handling and defined review paths.
Sample outputs
Extraction and verification specification · Provenance model · Exception workflow · Evaluation dataset design
E03
Ontology & Knowledge Engineering
Give AI the domain semantics needed to interpret entities, relationships, definitions and decision rules consistently.
Sample outputs
Domain ontology · Knowledge model · Semantic mappings · Evidence-aware retrieval design
E04
AI Capability, Maturity & Target Operating Model
Use structured assessment, including AIF7™ where appropriate, to distinguish missing evidence, capability constraints, accountability gaps and practical investment priorities.
Sample outputs
Baseline · Gap and root-cause analysis · Responsibility map · Prioritised roadmap
E05
Enterprise AI Transformation & Industrialisation
Turn a defined AI decision or programme into repeatable, governed enterprise operation with ownership, controls, evaluation and lifecycle management.
Sample outputs
Target operating model · Governance and control design · Deployment plan · Adoption and measurement framework
E06
Data & Risk Analytics
Structure financial, operational and risk information into transparent analytical views that support accountable business decisions.
Sample outputs
Analytic specifications · Validated measures · Reconciliation controls · Dashboards and decision-support models
Applied where decisions carry consequences.
The same expertise is applied differently in each sector, depending on the evidence, terminology, rules and authority involved.