The Deep Heuristics Assurance Platform
One institution. The entire AI lifecycle.
Independent AI trust and assurance across the entire AI lifecycle — from trust foundations and end-to-end lifecycle assurance to enterprise AI trust, aligned with global AI standards and regulations.
Architecture
How the platform is organised
Four concentric layers. At the centre, the trust foundations every assessment rests on. Around them, assurance across the lifecycle. Around that, the enterprise controls that make assurance durable. Outermost, the standards and regulations the whole structure answers to.
The four layers
Reading the architecture from the inside out
- Trust foundations
- Trusted AI — the properties an AI system must hold for reliance on it to be reasonable: assurance, governance, safety, security, reliability, compliance, privacy, and risk management.
- Lifecycle assurance
- End-to-end AI lifecycle assurance — strategy, model verification and validation, explainability, fairness and bias testing, robustness testing, red teaming, prompt security, hallucination and adversarial testing, data quality evaluation, and performance benchmarking.
- Enterprise AI trust
- Enterprise controls — board oversight, use case assessment, data governance, model development and training validation, testing, deployment assurance, incident response, procurement assurance, third-party assurance, internal audit, continuous monitoring, model change management, and model retirement.
- Standards & regulation
- The external frame — ISO/IEC 42001, ISO/IEC 23894, ISO 31000, ISO/IEC 27001, the NIST AI RMF, the EU AI Act, OECD AI Principles, and IEEE ethics standards.
Modules
Nine modules underneath every engagement
The platform is the machinery our assessors work in. Clients see its outputs — reports, ratings, dashboards, and evidence — and can reach the same data programmatically.
Why a platform
Consistency is what makes an opinion comparable
An assessment that depends on which assessor performed it is an opinion about a person, not about a system. The platform holds the frameworks, criteria, thresholds, and evidence rules constant, so two systems assessed six months apart can honestly be compared.
- Versioned assessment criteria
- Reproducible test procedures
- Tamper-evident evidence trail
- Consistent severity thresholds
- Peer review before issue
- Full audit history
Deploy AI with confidence.
Start with an independent assessment of your highest-stakes AI system.