AnnexOps Compliance

Real-time monitoring for every AI system you deploy

Article 72 requires providers to monitor high-risk AI systems post-deployment. AnnexOps streams telemetry from your SDK, detects drift and boundary violations, and surfaces them in your compliance dashboard.

✓ Article 72 compliant

✓ Drift detection

✓ Incident reporting (Art. 73)

What gets monitored

From telemetry to compliance evidence automatically

SDK telemetry ingestion

The AnnexOps SDK streams prediction events, input distributions, and output distributions to the monitoring pipeline. Every event is timestamped and correlated to your system registration.

Performance drift detection

Configurable thresholds for accuracy, fairness metrics, confidence distributions, and data drift. Automated alerts when monitored values exceed your defined bounds.

Incident reporting (Art. 73)

When a serious incident occurs, AnnexOps pre-populates the Article 73 incident report and routes it to the correct EU member state market surveillance authority.

Compliance Health Score

A 0–100 score computed from obligation completion, monitoring event status, and evidence quality. Updated in real-time. Shareable with investors and regulators.

Monitoring capabilities

Six monitoring capabilities out of the box

SDK telemetry streaming

Integrate the AnnexOps SDK in one line of code. Prediction events stream to your monitoring pipeline automatically. Zero manual data export required.

Drift and fairness monitoring

Monitor accuracy drift, fairness metrics (demographic parity, equalised odds), confidence score distributions, and data distribution shift. Configurable per-system thresholds.

Article 73 incident reporting

Pre-populated incident report when a serious incident is detected. Routes to the correct EU member state authority contact based on the system's deployment country.

Compliance Health Score

Real-time 0–100 score across obligation completion, monitoring status, and evidence quality. Embed the score widget in your investor dashboard or trust centre.

Post-market monitoring log

Article 72 monitoring log maintained automatically. Every anomaly, threshold breach, and corrective action is recorded and linked to the relevant obligation.

Boundary violation detection

Define your AI system's intended purpose boundary. AnnexOps detects when predictions fall outside intended use scope and flags them for human review.

Integrations

Works With Your Existing Stack

  • 🐙 GitHub Actions
  • 🦊 GitLab CI
  • 🤗 HuggingFace
  • 🧠 Anthropic Claude
  • 🌟 Mistral AI
  • ☁️ AWS SageMaker
  • 📊 Grafana
  • 🔴 Jira
  • 💼 Linear
  • 🔔 Slack
  • 🔷 Google Vertex AI
  • 🤖 OpenAI API

FAQs

Some Frequently Asked Questions and Their Answers

Why is continuous AI monitoring required under the EU AI Act?

The EU AI Act requires organizations to ensure that AI systems remain compliant throughout their lifecycle. Since AI models can change behavior over time due to new data or retraining, continuous monitoring is essential to detect risks and maintain compliance after deployment.

How does AnnexOps function as an AI monitoring platform for compliance?

AnnexOps acts as a real-time AI monitoring platform, tracking system behavior, outputs, and performance metrics. It continuously evaluates whether AI systems remain within their classified risk boundaries and triggers compliance actions when deviations occur.

What types of risks can AI monitoring detect?

AnnexOps monitoring detects:

  • model drift
  • unexpected output patterns
  • bias or anomaly signals
  • changes in system usage
  • deviations from expected behavior

This helps organizations identify compliance risks early.

How is AI monitoring different from traditional system monitoring?

Traditional monitoring focuses on uptime and infrastructure performance. AI monitoring focuses on decision behavior and outcomes, ensuring that AI systems produce consistent, fair, and compliant results aligned with regulatory expectations.

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News & Articles

Monitor every AI system. Prove it with evidence.

Connect your first system via the SDK and see live monitoring in under 10 minutes.