Product
Everything you need to run an AI feature in production
Five capabilities that share one data model. Instrument once, and tracing, evals, prompts, datasets and alerts all work off the same traces.
Capabilities
Observability
Search, filter and inspect every LLM call your application makes, with cost and latency attached.
Evaluations
Score outputs with LLM judges, code assertions or human review, and compare runs before you ship.
Prompt management
Version-controlled prompts with diffs, review and rollback, decoupled from your deploy cycle.
Tracing
Nested traces for agents, chains and tool calls, so a ten-step run reads like a stack trace.
Datasets
Turn real production traces into golden datasets, then use them as your regression suite.
How the pieces fit
Cloudmind is built around a single primitive: the trace. Everything else is a view on top of it.
- Your application calls a model. The SDK records a trace.
- That trace carries the prompt version that produced it, so you always know which revision was live.
- Interesting traces get promoted into a dataset with one click.
- Datasets are what your evaluations run against, in CI or on demand.
- Eval scores flow back into monitors, which alert when production quality drifts.
Because it is one data model rather than five products bolted together, you never have to re-instrument to unlock the next capability.
Stop guessing whether your AI feature got better
Free for 50,000 traces a month. No credit card, no sales call, five minutes to your first trace.
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