Scorable

Scorable is a platform that automatically evaluates and scores the outputs of large language model (LLM) applications. Instead of relying on manual checks or hoping your AI behaves correctly, Scorable inserts calibrated 'judges' into your AI pipeline. These judges analyze every response for specific problems like hallucinations, policy violations, and unclear language, providing a numerical score and a plain-English explanation for each issue. This happens in real-time, giving developers immediate visibility into what their AI is actually telling users.

The tool works by letting you describe what a 'good' response looks like in plain language. Scorable then automatically generates the evaluators for you. A key differentiator is that these evaluators are calibrated against a labeled dataset before deployment, which aims to solve the inconsistency problems of simply prompting another LLM to do the judging. This calibration process means scores are more reproducible and trustworthy. Integration is designed to be simple, with support for TypeScript, Python, and common AI frameworks, promising setup in under two minutes.

This is most useful for teams that have shipped AI features but lack a systematic way to ensure their quality and safety. It helps product managers and developers move from reactive problem-solving (waiting for user complaints) to proactive quality control. By surfacing issues by criticality and frequency, Scorable helps teams focus their efforts on fixing the most important problems first, whether that's gating deployments, blocking bad responses automatically, or just tracking performance trends.