Observe × Evaluate — Protecting AI Application Quality Across the Full Lifecycle
LLM upgrades, Agent iterations, Prompt changes — every update can trigger unforeseen quality regressions. Our eval-observability platform unifies observability with evaluation, continuously protecting AI application quality from CI/CD testing through production operations. Built on the OpenTelemetry standard, broadly compatible with all major LLM frameworks and Agent platforms, ready out of the box.
Based on OpenTelemetry and GenAI Semantic Conventions, broadly compatible with all major LLM frameworks and Agent platforms. Converts traces/spans directly into evaluation metrics — observability data becomes evaluation evidence, no duplicate data infrastructure needed.
Automatically runs full regression after every model upgrade, Prompt optimization, or Agent architecture change to prevent capability regressions. Seamless CI/CD integration ensures objective quality validation before every release, significantly reducing production incidents.
Real-time tracking of hallucination rates, Agent task completion, latency, and costs in production, with automatic alerting and rapid root-cause analysis. Supports controlled A/B experiments on Prompt strategies, RAG configurations, and model versions to drive data-backed continuous improvement.
Auto-sample from production traces, expert annotation interface, and public benchmark integration (MMLU, HumanEval, RAGAS). Full lifecycle management with version control, data lineage, and quality review ensures evaluation coverage stays relevant as your business evolves.
Collect complete traces of LLM calls and Agent executions via OpenTelemetry SDK, compatible with all frameworks following GenAI Semantic Conventions
Auto-sampling + expert annotation + public benchmark integration, versioned full-lifecycle evaluation dataset management
Multi-dimensional metrics (accuracy, hallucination, latency, cost), batch regression and A/B experiments running in parallel
Real-time tracking of key quality metrics, configurable alert thresholds, quality trend visualization dashboard
Controlled comparison of multiple LLM/Agent design versions, optimal design recommendation based on statistical significance analysis
Full coverage from CI/CD testing → staged rollout → production operations, queryable audit logs and actionable improvement recommendations
LLM/Agent Frameworks
LLM Providers
Eval Benchmarks
Observability Tools
CI/CD Integration
After every LLM upgrade, Prompt optimization, or Agent architecture change, integration regression tests automatically verify core capabilities have not regressed — ensuring every release has objective quality backing and significantly reducing production incidents from model changes
Through full OpenTelemetry integration, monitor hallucination rates and Agent task completion in real time. When anomalies occur, complete trace chain and evaluation dimension analysis enables teams to pinpoint root causes in minutes, rapidly verify fixes, and close the detect → diagnose → verify loop
Run controlled A/B evaluations across multiple Agent versions with different Prompt strategies, RAG configurations, and tool setups — select the optimal design based on objective data, eliminating guesswork from the tuning process
Build continuously evolving enterprise evaluation datasets through automatic production traffic sampling, expert annotation, and public benchmark integration — ensuring evaluation coverage stays high and relevant as your business scales
Book a personalised demo with our product team and explore how it fits your enterprise environment.
No credit card required · Setup in under 48 hours · Cancel anytime
