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 3 completely silent data pipelines, 82 runtime violations, and a calibration engine returning hardcoded defaults for months.

Sound Familiar?

"Our health endpoint said HEALTHY — but no data had moved in weeks"

— Silent Pipeline

"99 calibration results. Every single one was a hardcoded default."

— Default Masquerading as Data

"1,218 evolution cycles. Zero diversity. Same mutation type every time."

— Activity ≠ Effectiveness

"Tests passed. Dashboards green. Three 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 →

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 the Platform →

Start With a Silent Wiring Diagnostic

Find out if your AI-generated code is silently failing. We'll analyze your codebase for wiring failures, silent pipelines, and behavioral gaps — and give you a plan to fix them.

Get Your Diagnostic

We 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.

3 Silent pipelines found
112 Issues fixed in one sprint
82 Runtime violations caught
100% Flow verification
4 Failure types classified
See Full Metrics →

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 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.

2 August 2026

High-risk AI obligations take effect. Penalties reach €35M or 7% of global turnover.

Timeline

Feb 2025
Prohibited practices banned
Aug 2025
GPAI model obligations active
Aug 2026
High-risk AI obligations (Annex III)
Aug 2027
Regulated product AI, legacy GPAI

Penalties

€35M or 7%
Prohibited practices
€15M or 3%
High-risk non-compliance
€7.5M or 1%
Incorrect information
EU AI Act →

EU AI Act Requirements Addressed

Article 9 Risk Management

Continuous risk identification and mitigation

Doubt scoring predicts failure before it happens. 57,000+ patterns track what works.

Article 12 Record-Keeping

Automatic logging of AI system operation

99.8% capture rate. Immutable audit trails. Every decision logged.

Article 13 Transparency

Clear information about AI capabilities and limitations

Counterfactual explanations generated automatically. 'Why was this decision made?'

Article 14 Human Oversight

Meaningful human control over AI operation

Cross-provider stop commands. Brake engagement in 50ms. Control that actually works.

Article 15 Accuracy & Robustness

Consistent performance across conditions

Calibration monitoring detects drift. 11-dimension audit ensures quality.

Provider Tools Cannot Assess Provider Systems

Article 31(5) 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.

CABs for AI →

Infrastructure We Use Ourselves

99.8%
Capture Rate
Near-complete audit trail coverage
8
Patents Filed
Protecting the methodology
100%
Prediction Pairing
Every AI decision gets an outcome
50ms
Brake Response
Cross-provider stop command latency

Beyond EU AI Act

EU AI Act

Available

Full Annex III coverage, Article 9-15 mapping

ISO 42001

Available

AI Management System, 39 Annex A controls

SOC 2

Available

Trust Services Criteria, automated evidence collection

FedRAMP

Roadmap

NIST 800-53 mapping, US government requirements

Ready for August 2026?

Get an assessment of your AI systems against EU AI Act requirements.

Request Assessment