AI Monitoring

Know how your AI behaves after deployment

Continuously evaluate real sessions for quality, safety, task performance, and required behaviours. Track trends across versions, inspect the traces behind failures, and turn production issues into better tests.

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See all the tools to turn production traces into measurable quality signals

Synthetic Datasets

Thousands of test cases and simulated conversations generated from our Simulation Engine or your own product specs and files.

Custom metrics

Define your own scorers, thresholds, and quality criteria, or just let the Galtea Simulation Engine build them automatically from your product specs.

Traces

Plug into the logs and traces you already collect, with no second instrumentation effort.

Versions

Re-run the same test suite automatically on every prompt, model, or pipeline change, so regressions get caught before they ship.

Human reviews

Send the hard or flagged cases to expert reviewers, and use their verdicts to sharpen how quality gets scored over time.

GitHub Actions

Run evaluations automatically on every pull request, so a quality or safety regression is blocked before it reaches production.

Monitors

Monitor your production traffic automatically, automatically surface patterns in production, and what's driving them, before your users feel it.

Monitor sensitive AI systems without giving up control

ISO 27001 certified

Independently audited security controls across the full platform.

GDPR compliant

Data processing agreements, retention controls, and right-to-erasure built in.

Self-hosting & Private tenant

Deploy in your own cloud or VPC. Your data never leaves your infrastructure.

Premium support

A implementation plan tailored to your stack with a dedicated engineer team.

SSO & MFA

Single sign-on via your existing identity provider, with multi-factor authentication.

Service Level Agreement

Guaranteed response times with escalation paths for production incidents.

Keep your quality standard independent from your providers

Any AI architecture

Evaluate conversational agents, RAG pipelines, voice agents, and document processing systems. No matter how complex the architecture.

Model agnostic

Compare performance across different models with the same test suite, so you always know which model works best.

CI/CD ready

Plug evaluations into your pipeline with GitHub Actions, GitLab CI, or any CI system. Catch regressions before they reach production.

Frequently asked questions

What does Galtea monitor?

Galtea tracks AI quality, safety, performance, and defined behaviors across live systems and versions.

Can I monitor production traffic?

Yes. Connect your application traces and assess real interactions against the metrics that matter to your use case.

Is monitoring only for production?

No. Use the same evaluation framework before release, during testing, and after deployment.

Can I define my own monitoring metrics?

Yes. Create custom metrics, thresholds, and evaluation criteria for your product.

What kinds of AI products can Galtea monitor?

Galtea can evaluate and monitor AI products including RAG assistants, chatbots, voice agents, multi-agent systems, document-processing workflows, copilots, and other LLM-powered applications.

Is Galtea only for technical teams?

No. Developers, QA, product, risk, and compliance teams can work from a shared view of AI quality and evidence.

Can Galtea support audit and compliance workflows?

Galtea provides the evaluation & monitoring data and traceability teams need to support internal reviews and evidence requirements.

Know how your AI behaves after deployment

Monitor every type of high-stakes AI system

See all the tools to turn production traces into measurable quality signals

Monitor sensitive AI systems without giving up control

Monitor AI where reliability is non-negotiable

Keep your quality standard independent from your providers

Frequently asked questions

Learn how teams in regulated industries monitor their AI products with Galtea