LLM Evaluation & Observability
LangSmith, Tracing, RAGAS
You can't improve what you can't measure. We build evaluation pipelines that tell you exactly how your AI systems perform—and catch regressions before users do.
See LLM Evaluation in Action
12+ RAGAS 2025 metrics with LangSmith & Traceloop observability
What Gets Measured
Comprehensive metrics for AI system quality
Accuracy
Are answers correct? Factual accuracy, relevance, and task completion rates.
Groundedness
Are claims supported by sources? Hallucination detection and citation accuracy.
Retrieval Quality
Are we finding the right documents? Recall, precision, and relevance scores.
Cost & Latency
How much does it cost? How fast is it? Token usage and response time tracking.
What We Deliver
Complete evaluation infrastructure
Evaluation Datasets
- Curated test cases from your real data
- Edge case and adversarial examples
- Version-controlled golden datasets
Custom Judges
- LLM-as-judge evaluators
- Domain-specific scoring criteria
- Human evaluation integration
CI/CD Integration
- Automated evaluation on every PR
- Quality gates before deployment
- Regression alerts and dashboards
Tracing & Telemetry
See exactly what your AI systems are doing
Request Tracing
Follow every request from input to output. See each step, decision, and tool call.
Token Analytics
Track token usage per request, user, and feature. Optimize costs with data.
Error Tracking
Catch failures, timeouts, and unexpected responses. Debug with full context.
Performance Monitoring
Latency percentiles, throughput metrics, and capacity planning data.
Preventing Regressions
Because 'it worked yesterday' isn't good enough
Technologies We Use
FAQ
Do we need evaluation if our AI 'seems to work'?
Yes. 'Seems to work' breaks in production. Evaluation catches edge cases, measures improvement, and proves value to stakeholders.
How do you create evaluation datasets?
From your real data, production logs, and expert input. We identify representative cases, edge cases, and failure modes specific to your domain.
Can you integrate with our existing CI/CD?
Yes. We integrate with GitHub Actions, GitLab CI, CircleCI, and others. Evaluation becomes part of your normal development workflow.
What's the ROI of evaluation infrastructure?
Fewer production incidents, faster debugging, confident deployments, and data to prove AI value. Most teams see ROI within weeks of setup.
Fixed Price
Delivered in 2-3 weeks
50% upfront, 50% on delivery. Ongoing monitoring costs separate.
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