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Make AI responses measurable

Stop relying on manual vibe checks. Scorable replaces guesswork with automated, metric-driven judges that block hallucinations before customers see them.

From the community

Don't just log outputs. Judge them.

Our specialized Judges sit between your AI and your user, scoring every interaction against your specific policies.

USER INPUT

"Summarize the Q3 report."

LLM RAW OUTPUT

"Revenue grew by 20% due to the new product launch."

SCORABLE LOGIC LAYER

"judge_verdict": {
  "score": 0.2,
  "justification": "Statement not found in source text. Source says revenue was flat."
}
Docs

Python

JavaScript/TypeScript:

How It Works

  1. Your application sends requests to our proxy URL instead of OpenAI's
  2. Your tailored judge improves the response automatically based on it's feedback

Start by creating a judge by describing what you want to measure


Know what to fix, instantly.

Scorable analyzes your evaluation results and surfaces actionable insights — delivered to your dashboard or Slack.

INSIGHTS 12/12/2025 — 19/12/2025

Wins
  • •Overall quality improved vs. the previous period: average score increased ~18.9% to 0.777.
  • •Clear high performers: "Email Response Judge" (avg ≈ 0.858), "Product Recommendations Judge" (avg ≈ 0.826).
  • •Release v1.2 showing consistent quality improvements across all judges.
Issues
  • •"Returns Policy Judge" (avg ≈ 0.496) — likely impacting customer experience in refund flows.
  • •"Appointment Scheduling Judge" (avg ≈ 0.651) (staging environment) with high volume — needs attention before scaling.

Enterprise-Grade Sovereignty

SOC 2 Type IIGDPR CompliantVPC DeploymentModel Agnostic