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Prompt & Evaluation Management

Version, evaluate, and monitor — from playground to production.

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TRUSTED BY ENTERPRISE DATA TEAMS WORLDWIDE

From first prompt to production quality — without stitching tools together.

Every capability your team needs lives in one coherent workflow.

Interactive prompt playground

Test models side by side. Compare quality, cost, and latency before anything ships.

Prompt versioning linked to traces

Every version is stored with full history. Reproduce past behavior. Audit exactly what ran when something went wrong.

Flexible evaluation metrics

Use built-in metrics or define your own. Heuristic checks, LLM-as-judge, or both.

Offline and online evaluation

Run regression suites before changes ship. Catch quality drops in CI, not in customer escalations. In production, the same metrics run continuously — surfacing regressions and drift as they happen.

Datasets that grow from production

Build, version, and reuse datasets across experiments and regression suites. Promote production traces directly into test sets. Every failure strengthens the next suite.

Trace annotation and alerting

Annotate traces with labels, feedback, or scores. Set thresholds for quality, latency, cost, and reliability. When production crosses the line, you get an alert with traces ready to investigate.

The development loop, end to end.

Develop

Iterate in the playground. Test across models, inspect outputs, refine. Every revision is versioned automatically.

Evaluate offline

Run against curated datasets. Score with statistical metrics, LLM-as-judge, or custom evaluators. Confirm the change actually improves quality.

Ship and monitor

Promote to production. The version is captured on every trace. Online evaluations run continuously against the same metrics used offline.

Improve

Surface low-scoring traces, annotate with human feedback, promote failures into your dataset. Each iteration starts with stronger coverage than the last.

No lock-in. No black boxes.

Built on the primitives your team already uses — with the portability and auditability you need at scale

LangChain

LangGraph

LlamaIndex

OpenAI

Anthropic

CrewAI

AutoGen

Google ADK

Built different. For teams that care about quality.

Offline and online evaluation in one place

Stop stitching together a playground, a CI tool, and a production monitor. The same metrics, datasets, and prompt versions move from development through regression testing to live production — no re-implementation.

Datasets that grow from production.

Failures get promoted directly into evaluation datasets. Every incident strengthens the test suite that prevents the next one

Quality as a first-class signal.

Prompt versions, evaluation scores, and human feedback live on traces alongside cost, latency, and errors. Quality regressions are debuggable the same way infrastructure regressions are.

Dominate with Data

40%

reduction in pipeline
downtime

30%

faster time-to-model
deployment

25%

lower cluster costs

99.9%

SLA adherence on
migrated workloads

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