Production AI evaluation

Know if your AI is actually working.

LiveEvals runs every production interaction through your own judgment criteria — continuously, not just before launch.

Get started →Bring your own API key. No card required.
Is the valuation reasonable?
The DRHP doesn't disclose price band or P/E yet — placeholders throughout...
RELEVANT82%
What are the main red flags?
Retrieved sections cover ESG policy, not risk factors — answer flags the gap...
NOT RELEVANT92%
Who are the promoters?
Promoter holding of 68.4% disclosed on page 142, names listed...
RELEVANT95%
How does revenue compare to peers?
Peer comparison data was not present in retrieved chunks...
NOT RELEVANT88%
What does the GMP signal?
GMP of ₹4, a 3.5% premium — modest, suggests lukewarm sentiment...
RELEVANT79%
Should I subscribe to this IPO?
Given medium risk and weak subscription, a cautious wait-and-watch...
RELEVANT86%
Is the valuation reasonable?
The DRHP doesn't disclose price band or P/E yet — placeholders throughout...
RELEVANT82%
What are the main red flags?
Retrieved sections cover ESG policy, not risk factors — answer flags the gap...
NOT RELEVANT92%
Who are the promoters?
Promoter holding of 68.4% disclosed on page 142, names listed...
RELEVANT95%
How does revenue compare to peers?
Peer comparison data was not present in retrieved chunks...
NOT RELEVANT88%
What does the GMP signal?
GMP of ₹4, a 3.5% premium — modest, suggests lukewarm sentiment...
RELEVANT79%
Should I subscribe to this IPO?
Given medium risk and weak subscription, a cautious wait-and-watch...
RELEVANT86%
The gap

Dev-time testing is solved. Production is where teams fly blind.

Most eval tools are built and judged on how well they catch regressions before launch. Almost none of them have a real answer for what your AI is doing right now, with real users, today.

Well-served

Golden datasets, regression suites, CI gates — testing before you ship is a mature, well-funded category.

Still open

Continuous judgment of live traffic, with a structured confidence signal that tells you when to actually look closer.

How it works

Three steps. No dev-time-only test suite required.

01

Push a trace

One API call, right after your AI system answers. You control exactly what gets sent.

requests.post(
  ".../traces",
  json={"input": {...},
        "output": {...}})
02

Write what "correct" means

One eval prompt per system, in your own domain language. Start from a template or write your own.

03

Get judged automatically

Every trace scored against your rubric, on a schedule or on demand — label, reasoning, and confidence, every time.

Structured output

Not just pass or fail. A reasoned verdict, every time.

A real judged trace, exactly as LiveEvals stores it — nothing simplified for the marketing page.

Question
What are the main red flags?
Retrieved evidence
ESG/sustainability policy, employee safety protocols, shareholder voting procedure — no Risk Factors section
Reasoning
Retrieved chunks contain ESG/sustainability policies, not the DRHP's Risk Factors section. The answer correctly acknowledges this, but introduces GMP and subscription figures not present in the retrieved evidence.
NOT RELEVANTConfidence 92%
Ownership

You bring the judgment. We bring the infrastructure.

A platform that graded your AI without understanding your domain would be a black box. This one doesn't try to.

LiveEvals owns

  • The harness, the schedule, the dashboard
  • Structured, validated output every time
  • Drift detection and stale-eval flags
  • Your own API key, encrypted, never logged

You own

  • The eval prompt, in your own vocabulary
  • What each label means
  • Your pass threshold, your risk tolerance
  • The golden examples that define “correct”