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Keido Evaluation Engine

Your AI is running. Is it performing?

KEE scores every response your AI systems produce, in production, against the four things that decide whether people trust them: speed, accuracy, coverage and reliability. When a score moves, you know the same day, not after the wrong decision has been made.

Start a four-week evaluation pilot
Download the AI evaluation checklist

What it evaluates

If you can log a prompt and a response, KEE can score it.

KEE sits alongside any AI system that produces text or structured output: a search or retrieval-augmented assistant, a summariser, a classifier, an agent running multi-step tasks, or a model you have fine-tuned yourself.

Works with

  • OpenAI
  • Anthropic
  • Google
  • Open-weight models
  • Your own models

The four scores

Four scores, each tied to a business consequence.

  • 01

    Speed

    Time to first response and time to complete, by task type.

    Slow tools get abandoned. Speed is the first adoption signal.

  • 02

    Accuracy

    Whether the answer is correct, grounded in your sources, and free of fabrication.

    The score that decides whether a result can be acted on.

  • 03

    Coverage

    Whether the answer used everything relevant and left nothing important out.

    A correct but incomplete answer still produces a wrong decision.

  • 04

    Reliability

    How consistently the system performs across conditions, users and edge cases, rolled into one confidence index.

    The number a leader can read without knowing the other three.

What you see

One view for leaders. The detail for teams.

  • Leaders

    A single view: which systems are performing to expectation and which have moved.

  • Teams

    Which queries, which sources, which conditions caused the shift, and a ranked list of what to fix first.

  • Alerts

    Configurable by threshold and by audience.

More than a dashboard

  • A dashboard

    Reports what happened.

  • KEE

    Runs the evaluation continuously and tells you what to change.

Which prompts to tighten, which sources to update, which edge cases need a guardrail. As your data grows and demand rises, KEE re-baselines so a score still means the same thing six months in.

Built for governance

Every score is auditable.

  • Every score, alert and evaluation run is logged and exportable for audit
  • Multi-model and multi-dataset comparison, so you can test a model change before it ships
  • Trend analysis by team, task and time, for targeted optimisation
  • Runs inside your environment; evaluation data never leaves it

How an engagement runs

Four weeks to a leadership readout.

  1. Week 1 Connect KEE to one system in production and agree the rubrics with the owning team
  2. Weeks 2 to 3 Baseline scores, tune thresholds, first alert review
  3. Week 4 Leadership readout with the reliability index and the top five fixes
  4. Ongoing Monthly or quarterly review, or hand over to your team

Next step

Put one production system through a four-week evaluation.

Start a four-week evaluation pilot
Download the AI evaluation checklist

The AI evaluation checklist

One page: the questions a leader should be able to answer about any AI system in production.

See the Evaluation API