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Measure Everything Your AI Agent Tells Customers

Stop relying on manual vibe checks. Scorable replaces guesswork with automated AI-driven judges that monitor behavior in production and prevent harmful content before customers see them.

From the community

You can never be sure if your LLM features are delivering quality results unless you check.

What teams run into

1.You're relying on experts to do “vibe checks,” but they are biased and slow.
2.Debugging your agent stopped being fun a while ago.
3.You have better things to do than become a data scientist.

Get visibility into the “black box” of AI agents and chatbots — so you can build better products.

Iterate quickly on your Agent KPIs to match your business needs.

Leverage evaluations to optimize LLMs, judges, and prompts for the best balance of quality, cost, and latency.

Ensure LLM workflows deliver quality outputs, prevent hallucinations, and maximize accuracy.

Step 1

Build AI judges in minutes, customized to your customer interactions.

The rich evaluation signals for compliance, hallucination detection, relevance - and custom agent failure modes.

Step 2

Embed the judges into your code to monitor AI in production.

Evaluate AI performance in real time, immediately identify issues that impact product quality.

Step 3

Detect and correct subtle errors in agent interactions.

Reduce 90% of manual work - only alert the human expert when necessary. Continue to improve your AI-powered products in production.

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

Your application sends requests to our proxy URL instead of OpenAI's
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

Watch 20 second introduction

Product

Resources

Legal

Community

Measure Everything Your AI Agent Tells Customers

Stop relying on manual vibe checks. Scorable replaces guesswork with automated AI-driven judges that monitor behavior in production and prevent harmful content before customers see them.

From the community

You can never be sure if your LLM features are delivering quality results unless you check.

What teams run into

1.You're relying on experts to do “vibe checks,” but they are biased and slow.
2.Debugging your agent stopped being fun a while ago.
3.You have better things to do than become a data scientist.

Get visibility into the “black box” of AI agents and chatbots — so you can build better products.

Iterate quickly on your Agent KPIs to match your business needs.

Leverage evaluations to optimize LLMs, judges, and prompts for the best balance of quality, cost, and latency.

Ensure LLM workflows deliver quality outputs, prevent hallucinations, and maximize accuracy.

Step 1

Build AI judges in minutes, customized to your customer interactions.

The rich evaluation signals for compliance, hallucination detection, relevance - and custom agent failure modes.

Step 2

Embed the judges into your code to monitor AI in production.

Evaluate AI performance in real time, immediately identify issues that impact product quality.

Step 3

Detect and correct subtle errors in agent interactions.

Reduce 90% of manual work - only alert the human expert when necessary. Continue to improve your AI-powered products in production.

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

Your application sends requests to our proxy URL instead of OpenAI's
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

Measure Everything Your AI Agent Tells Customers

From the community

You can never be sure if your LLM features are delivering quality results unless you check.

What teams run into

Build AI judges in minutes, customized to your customer interactions.

Embed the judges into your code to monitor AI in production.

Detect and correct subtle errors in agent interactions.

Don't just log outputs. Judge them.

Hallucination Detector

Returns Policy

Build Your Own

How It Works

Know what to fix, instantly.

Enterprise-Grade Sovereignty

Product

Resources

Legal

Community

Measure Everything Your AI Agent Tells Customers

From the community

You can never be sure if your LLM features are delivering quality results unless you check.

What teams run into

Build AI judges in minutes, customized to your customer interactions.

Embed the judges into your code to monitor AI in production.

Detect and correct subtle errors in agent interactions.

Don't just log outputs. Judge them.

Hallucination Detector

Returns Policy

Build Your Own

How It Works

Know what to fix, instantly.

Enterprise-Grade Sovereignty