AI Intelligence for the Enterprise.
Regurai connects AI to the business, data, architecture, risk and value around it — helping organisations see where AI operates, understand its impact, make better decisions and govern AI with confidence.
Understand. Connect. Assess. Decide. Govern. Prove.
A model change re-scores connected risk, control and value views.
Change one part of the enterprise and the connected areas re-score. Relationships. Dependencies. Consequences.
AI is governed in one place. Its consequences land everywhere else.
GRC, AI governance, data governance, enterprise architecture and finance each hold part of the picture. None of them holds the relationships between the parts — so the impact of an AI change has to be reassembled by hand, every time it is questioned.
Regurai sits above and between existing enterprise platforms, bringing their information into a connected, decision-ready context.
The eight questions leaders ask about AI.
Answered from one connected view of the enterprise, before any specialist terminology is needed.
- What is happening?
- See where AI runs across the organisation and what it is doing.
- What does AI affect?
- See the data, applications, technology, processes and people connected to it.
- What could change?
- Test a change before committing to it and see what moves with it.
- What could go wrong?
- Understand risk, dependency and resilience exposure in one place.
- What is the business impact?
- Understand cost, benefit and value alongside risk, not separately.
- What decision do we need to make?
- Bring the options, trade-offs and context into one governed decision.
- What should we govern?
- Apply controls, approvals and accountability where they matter most.
- What evidence do we have?
- Retrieve evidence of what happened, who approved it and why.
Seven kinds of intelligence, one connected model.
Regurai keeps AI alongside the enterprise context, risk, decisions, governance and evidence connected to it, and runs as a continuous cycle rather than a periodic exercise.
Understand what the organisation actually runs on, and what depends on what.
Enterprise Context
Enterprise architecture, capability mapping, application and technology portfolio, dependency analysis.
See where AI operates, what it is doing and where intervention may be required.
AI Intelligence
AI and model inventory, AI workforce, agent observability, AI-enabled applications.
Know the data behind AI decisions — its meaning, quality, ownership and permitted use.
Data Intelligence
Data catalogue, business glossary, data quality, lineage, data architecture.
Understand what could go wrong, what would be affected and how severe it would be.
Risk & Impact
Risk and impact assessment, resilience, exceptions, portfolio heatmaps, scenario simulation.
Make decisions with the business, economic and operational context attached.
Decision Intelligence
Decision workspaces, AGEE economics, simulation, reporting and analytics.
Apply controls, approvals and accountability where they are needed.
Governance
AI governance, data governance, financial governance, controls library, approvals.
Show what happened, who decided it and on what basis.
Evidence & Assurance
Audit explorer, audit log, evidence vault, framework coverage, reporting.
See the enterprise model, the intelligence cycle and the product modules in detail.
Understand
Discover AI systems, data, applications, processes, technologies, risks and controls, and establish ownership for each.
What Regurai can actually do.
Seven working areas of the platform. AI governance is one of them, sitting alongside the enterprise, data, risk, decision and evidence intelligence around it.
Leadership sees the enterprise as it is today, with exceptions surfaced rather than discovered later.
Command
Dashboard · Digital Twin · AI Workforce · AI Agent Observability · Exception Center
Change is planned against real dependencies, so consequences are known before commitment.
Enterprise Architecture
EA Command Center · Capability Map · Application & Technology · Data Architecture · Dependency Analysis · Portfolio Heatmap · EA Copilot
AI decisions rest on data whose origin, quality and permitted use are known.
Data Governance
DG Command Center · Data Catalog · Business Glossary · Data Quality · Governance Exceptions · DCAM Maturity · Governance Automation
Regulatory positions are supported by mapped controls and retrievable evidence.
EU / UK Financial Governance
EU/UK Model Risk Management · Operational Resilience · Consumer Duty & Fairness · Financial Crime · Compliance Hub · Controls Library · Framework Coverage · Evidence Vault
Every AI system in use has an owner, an assessed risk position and a recorded decision to run it.
AI Governance
Model Inventory · AGEE · Risk & Impact · Approvals
Boards, auditors and regulators receive evidence from the same model the business runs on.
Analytics & Tooling
Audit Explorer · Audit Log · Simulation Lab · Risk Center · Reports · Audit Log Viewer
Teams adopt the platform without depending on tribal knowledge.
Learn
Help Centre
Govern every AI system, and everything it touches.
AI is being adopted faster than governance can follow. Model registers, risk registers, data catalogues, control libraries and architecture repositories each hold part of the answer, and none of them hold the relationships between them.
AI Model Governance
A governed register of models with ownership and lifecycle state.
AI Agent Governance
Constrain what autonomous agents may do, and against which systems.
AI Risk Management
Risk assessed against dependencies, not in a standalone register.
Control Intelligence
Controls connected to the AI systems they actually constrain.
Regulatory Intelligence
Obligations mapped to policies, controls, systems and evidence.
Data Foundations for AI
The data behind each AI system, with lineage and sensitivity.
Lifecycle & Approvals
Structured assessment, review and approval with separation of duties.
Audit Trails & Evidence
Prove what happened, who approved it and on what basis.
Change one AI model. Understand the business consequence.
Trace a single model change from the AI system through the applications, data, risks, controls and obligations it touches, to the evidence and business impact it produces.
A credit-decisioning model is upgraded to a new version.
One change to one AI system. In most organisations, the consequences sit in six different tools and four different teams. Here is the same change traced across one connected model.
Select a step to see what the change reaches from there.
The model change is registered
The model version, owner, purpose, training data lineage and intended decision scope are recorded against the existing AI system entry — not as a new, disconnected record.
- Model version and owner
- Intended decision scope
- Change request and approver
The organisation knows an AI system changed, and who is accountable for it.
Built for complex organisations, not one industry.
Regurai is designed for organisations where AI, data, technology, regulation, risk and operational complexity intersect.
Financial Services
Banks, insurers, asset managers, payments and fintech.
View industryGovernment & Public Sector
Government departments, agencies, regulators and local authorities.
View industryHealthcare & Life Sciences
Hospitals, health systems, pharmaceutical companies, medtech and research organisations.
View industryTelecommunications
Network operators, telecom providers and digital infrastructure businesses.
View industryEnergy & Utilities
Utilities, infrastructure operators and critical asset owners.
View industryTransport & Logistics
Airlines, rail operators, airports, ports and logistics providers.
View industryManufacturing
Advanced manufacturing, automotive and complex supply chains.
View industryRetail & Consumer
Large retailers, e-commerce operators and consumer AI and data environments.
View industryTechnology & SaaS
Software companies, cloud providers and organisations embedding AI into products.
View industryProfessional Services
Consulting, legal, accounting and other highly regulated professional organisations.
View industryDesigned for organisations where decisions must be defensible.
Trust is built into the model: role-based access, separation of duties, immutable audit records, evidence trails and traceable decisions.
Role-based controls
Deny-by-default access enforced server-side.
Immutable audit
Append-only records of decisions and approvals.
Evidence trails
Evidence produced as a by-product of governance.
Standards context
Aligned to recognised AI and risk frameworks.
Enterprise architecture
Multi-tenant, separated environments.
Integration capability
Sits between existing enterprise platforms.
Traditional platforms manage records.
Regurai connects decisions.