AI evals, observability & governance
We measure, monitor and protect every AI system, keeping accuracy, security and cost under control.
LANGFUSE
LANGSMITH
ARIZE PHOENIX
DEEPEVAL
RAGAS
LITELLM
GUARDRAILS
OPENTELEMETRY
MLFLOW
Expertise in AI evals, observability & governance
An agent can work well in a demo and fail in production. Our stack answers three questions with evidence: does it answer correctly, is it safe, and how much does it cost?
Evaluations
DeepEval and Ragas measure accuracy, grounding, and hallucinations on every change, before anything reaches production.
- DEEPEVAL
- RAGAS
Observability
Langfuse, LangSmith, Arize Phoenix, and OpenTelemetry trace every conversation, tool call, latency, and token usage.
- LANGFUSE
- LANGSMITH
- ARIZE PHOENIX
- OPENTELEMETRY
Security
Guardrails against prompt injection and data leaks, and masking of personal data before it reaches an external provider.
- GUARDRAILS
Cost (AI FinOps)
LiteLLM routes each query to the right model by complexity and budget, and MLflow manages model versions and experiments.
- LITELLM
- MLFLOW
Where we use it
Projects we've delivered
Taking BTH's agents to production, including Georgia, which evaluates elevator pitches against fixed criteria, and building an evaluation architecture for healthcare models at Validate Health, with a base model, an evaluator and metrics, taught us that an AI system without measurement cannot be trusted. That's why every solution we deliver ships with evaluations and monitoring, and we apply the same discipline when auditing third-party agents.
