Your AI Code Passes Every Test. But Is It Actually Working?
We built 1.1 million lines with AI assistance. Health checks said HEALTHY. Tests passed. Then we built a behavioral verification system. And found 4 silently broken data pipelines, 82 runtime violations, and a calibration engine writing 17,952 records that nothing had computed.
Sound Familiar?
"Our health endpoint said HEALTHY. But no data had moved in weeks"
Silent Pipeline
"17,952 calibration records. Fresh, plausible, every one of them different. Not one of them computed."
Default Masquerading as Data
"131 mutations in sixty-three days. The operators kept varying. The population did not."
Activity ≠ Effectiveness
"Tests passed. Dashboards green. Four pipelines completely dead."
The Behavioral Verification Gap
These aren't hypothetical scenarios. They're what we found in our own 1.1M-line codebase. After tests passed and health checks said HEALTHY.
See How →7 Problems. 3 Layers. Complete Verification.
How CleanAim® Works
Verification That Proves
Not just rules. Behavioral proof that data actually flows through expected paths. Topology declarations + continuous liveness checks.
Context That Survives
92% automated handoffs, 100% restore rate. Your AI remembers across sessions, compactions, and model switches.
Learning That Compounds
57,000+ patterns captured. Each deployment improves failure prediction. Compound learning that gets better at preventing silent wiring over time.
Explore AI Code Audit Detection
AI-generated code that compiles, passes tests, and silently fails. We documented the problem across 1.1 million lines. And built the infrastructure to detect it.
See the ResearchWe Pointed It at Ourselves
We built a behavioral verification system and ran it against our own 1.1M-line codebase. Here's what it found.
Built for Teams Using AI Coding Agents
Engineering Teams
Stop babysitting your AI agent. Get reliable code that doesn't require constant oversight.
Regulated Industries
Audit trails that satisfy compliance. Every AI decision logged and traceable.
Development Agencies
Deliver AI-assisted code your clients can trust. Prove quality with metrics.
AI GOVERNANCE
AI You Can Prove
The EU AI Act doesn't just require paperwork. It requires proof that your AI systems behave as documented.
Most compliance platforms help you file documentation. CleanAim® installs the infrastructure that makes that documentation verifiable.
When auditors ask 'How do you know this is true?', you have the answer.
Existing platforms help you file paperwork for a building permit. CleanAim® installs the fire suppression system. Both are required, only one saves lives when things go wrong.
THE DEADLINE
2 December 2027
High-risk AI obligations take effect. Penalties reach €15M or 3% of global turnover.
Timeline
Penalties
WHAT WE COVER
EU AI Act Requirements Addressed
Continuous risk identification and mitigation
Doubt scoring predicts failure before it happens. 57,000+ patterns track what works.
Automatic logging of AI system operation
99.7% capture rate. Immutable audit trails. Every decision logged.
Clear information about AI capabilities and limitations
Counterfactual explanations generated automatically. 'Why was this decision made?'
Meaningful human control over AI operation
Cross-provider stop commands. The signal propagates in 50ms and a full stop across providers completes in under 5 seconds. Control that actually works.
Consistent performance across conditions
Calibration monitoring detects drift. 11-dimension audit ensures quality.
THE INDEPENDENCE PROBLEM
Provider Tools Cannot Assess Provider Systems
Article 31(4) requires that Conformity Assessment Bodies maintain independence from AI providers.
AWS monitoring tools assess AWS systems. Azure governance covers Azure deployments. GCP logging works for GCP infrastructure.
When the auditor's tools come from the same vendor as the system being audited, independence is compromised, not by intent, but by architecture.
CleanAim® is provider-independent by design. One governance layer that works across Claude, GPT, Gemini, and any other provider.
INDUSTRIES
High-Risk AI Applications
EU AI Act Annex III defines high-risk categories. We serve organizations in each.
Financial Services
Credit scoring, fraud detection, algorithmic trading
Fair lending compliance, explainable decisions
Healthcare
Diagnostic AI, treatment recommendations, triage
Patient safety, clinical validation
HR Technology
Resume screening, candidate ranking, performance assessment
Non-discrimination, bias auditing
Insurance
Risk assessment, claims processing, pricing
Actuarial fairness, explainability
PARTNERS
Who We Work With
Conformity Assessment Bodies
Provider-independent infrastructure for Article 31(4) compliance. Assess any AI system from any provider.
Audit & Accounting Firms
AI audit methodology and evidence collection. Defensible assessments your clients can rely on.
Insurance Underwriters
Quantifiable AI risk assessment. Price AI liability coverage based on actual system behavior.
THE PROOF
Infrastructure We Use Ourselves
COMPLIANCE MODULES
Beyond EU AI Act
EU AI Act
Full Annex III coverage, Article 9-15 mapping
ISO 42001
AI Management System, 39 Annex A controls
SOC 2
Trust Services Criteria, automated evidence collection
Ready for December 2027?
Explore how infrastructure-level compliance addresses EU AI Act requirements.
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