14 REGULATIONS. 4 CONTINENTS. ONE EVALUATION. — Colorado (June 30) · EU AI Act (Aug 2) · NYC LL144 · SR 11-7 · Texas · California · South Korea · UK · China · GDPR — View all →
Independent AI evaluation and certification

Five independent validators. Causal decomposition. Prescriptive remediation.

Independent consulting auditors provide rigorous evaluation — but require weeks of engagement per audit and can't scale. Governance platforms offer software tools — but aren't structurally independent. AI Asset Assurance combines both: genuine third-party independence with scalable evaluation technology. We decompose any deviation to its root cause and prescribe exactly how to fix it. This page explains the technical pipeline from submission to certification.

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PIPELINE SPECS
Independent validators5 models
Verification latencyPer-request
Deployment layers sealed6 layers
Consensus mechanismBFT median
DecompositionShapley attribution
OutputCause + fix + projection
THE CORE DIFFERENCE

Other platforms monitor what your AI outputs.
AI Asset Assurance verifies what your AI is.

Governance platforms monitor your AI's behavior and flag problems after they've affected production. Consulting auditors provide genuine independence — but require weeks of engagement and can't scale. AI Asset Assurance combines structural independence with proactive, scalable verification you can start in minutes.

REACTIVE MONITORING · GOVERNANCE PLATFORMS
Detects drift days or weeks later.
Someone swaps the model → metrics look normal for weeks
System prompt is modified → satisfaction scores improve — shows green
RAG index contaminated → errors below statistical threshold — invisible
3rd-party model updated → same endpoint — cannot detect at all
Safety filters lowered → looks positive — false refusal rate drops
Asks: "Is the AI behaving well?" — but can't tell you if the AI itself has changed.
PROACTIVE VERIFICATION · AI Asset Assurance
Catches changes on the next request.
Someone swaps the model → canary probes detect on the next request
System prompt is modified → hash mismatch breaks seal instantly
RAG index contaminated → retrieval fingerprint changes — caught immediately
3rd-party model updated → behavioral probes detect regardless of source
Safety filters lowered → config is a sealed layer — change breaks the seal
Asks: "Is this still the same AI that was certified?" — with cryptographic proof.
Per-request
Per-request verification
6 layers
Model · Prompt · RAG · Tools · Safety · Infra
Zero trust
Separate infrastructure, can't self-influence
What makes AI Asset Assurance different

They watch what your AI does. We verify it's still the same AI that was certified.

Governance platforms like Credo AI, Holistic AI, and OneTrust sell software to the companies they evaluate — creating a structural conflict of interest. Consulting auditors like BABL AI and ORCAA provide genuine independence but deliver bespoke engagements that take weeks. AI Asset Assurance combines structural independence with scalable, patent-protected evaluation technology delivered through a streamlined engagement process.

01 · DEPLOYMENT INTEGRITY

Certification means right now — not last quarter.

We seal your complete deployment stack — model fingerprint, system prompt, RAG index, tool permissions, safety filters, infrastructure attestation — and verify it on every request. If your model is updated, your prompt is changed, or your retrieval index is swapped, we detect it before the modified system processes a single production input. Reactive monitoring catches drift in days or weeks. Proactive verification catches changes on the next request.

Six layers sealed · Per-request verification · Proactive, not reactive
02 · STRUCTURAL INDEPENDENCE

Five validators with no commercial interest in the outcome.

Other platforms evaluate your AI using their own proprietary system — the company selling governance is grading the test. AI Asset Assurance uses five models from five different organizations, running on separate hardware, with Byzantine Fault Tolerant median consensus. The evaluator is structurally unable to influence its own scores. That's the independence regulators and customers require.

5 models · 5 separate VMs · BFT consensus
03 · CAUSAL DECOMPOSITION

Not just a score — a diagnosis and a prescription.

We compute the delta between inputs and outputs, isolate which variables cause deviations using Shapley attribution, detect cohort-level patterns, and deliver remediation recommendations with projected improvements. Other platforms tell you something is wrong. We tell you exactly what caused it and how to fix it.

Score → Cause → Remediation → Projected improvement
Evaluation process

Submission to certification in four steps.

Your AI system's outputs are evaluated by five structurally independent models with full causal decomposition.

01

Submit and seal

Provide input-output pairs via REST API. We fingerprint your deployment stack to create a sealed configuration verified throughout the certification period.

02

Independent evaluation

Five AI models — each on separate infrastructure with distinct architectures and training data — independently score your outputs across five compliance dimensions.

03

Diagnose and prescribe

Scores are aggregated via BFT consensus, then decomposed into causal findings: which inputs drive deviations, what cohort patterns exist — and specific remediation steps with projected score improvements for each.

04

Certify and monitor

Digitally signed certification with decomposed findings mapped to all applicable regulations — US state laws, EU AI Act, GDPR, and international frameworks. Sealed deployment verification maintains integrity for the full validity period.

Evaluation pipeline — five independent validators, BFT consensus, causal diagnosis, and remediation
INPUT/OUTPUT Customer AI pairs SEAL CHECK Fingerprint verify Per-request VALIDATOR 1 Constitutional compliance VALIDATOR 2 Value alignment VALIDATOR 3 Manipulation detection VALIDATOR 4 Behavioral consistency VALIDATOR 5 Harm avoidance BFT MEDIAN CONSENSUS Fault-tolerant DIAGNOSE Delta analysis Shapley attribution Cohort patterns Remediation steps CERTIFIED Digitally signed Art. 9–15 mapped 0.91 Separate hardware · Separate architecture · Separate training data
INPUT / OUTPUT
Customer AI pairs submitted for evaluation
SEAL CHECK
Fingerprint verification
Per-request
VALIDATOR 1
Constitutional
VALIDATOR 2
Value alignment
VALIDATOR 3
Manipulation
VALIDATOR 4
Behavioral
VALIDATOR 5
Harm avoidance
BFT MEDIAN CONSENSUS
Fault-tolerant aggregation
DIAGNOSE & PRESCRIBE
Delta analysis · Shapley attribution · Cohort patterns
Remediation steps with projected improvements
CERTIFIED
Digitally signed · All regulations mapped
0.91
How AI Asset Assurance fits

You've built governance. Now prove it works.

AI Asset Assurance is the independent evaluation layer that completes your compliance program.

Your AI governance process
PHASE 1
Build governance
Inventory AI systems, classify risk levels, create policies, build documentation
Credo AI · Holistic AI · OneTrust · IBM watsonx
PHASE 2
Internal assessment
Test for bias, validate accuracy, conduct risk assessments, document compliance
Your engineering + compliance team
PHASE 3 · AI Asset Assurance
Independent proof
Structurally independent evaluation with causal decomposition, sealed deployment, and verifiable certification
The evidence your customers and regulators ask for
OUTCOME
Compliant and credible
Regulatory conformity with independently verified evidence suitable for regulators across 4 continents — US, EU, UK, and Asia-Pacific
EU AI Act · LL144 · Colorado · SR 11-7 · Texas · California · Illinois · GDPR · UK · South Korea · China · Brazil · Canada
Governance platforms help you build compliance (reactive monitoring). AI Asset Assurance provides proactive independent proof that it works.
CapabilityYour governance platformYour internal teamAI Asset Assurance
AI system inventory and shadow AI discovery
Risk classification and policy management
Output monitoring and drift detection (reactive)
Compliance documentation and audit artifacts
Structurally independent evaluation (5 models, BFT)
Proactive deployment integrity verification
Causal decomposition with Shapley attribution
Remediation recommendations with projected improvements
Third-party verifiable sealed certification

Ready to see AI Asset Assurance evaluate your system?

Submit your AI system's input-output pairs. Five independent validators. Causal decomposition. Prescriptive remediation. Results mapped to every regulation that applies to you.

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