Deepchecks LLM Evaluation
Evaluate, monitor, and safeguard your LLMs
Continuously validate your LLM-based application throughout the entire lifecycle from pre-deployment and internal experimentation to production.
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Everything You Need for Continuous Evaluation of LLMs
LLM EvaluationÂ
A holistic solution for testing and
evaluating your LLMs, based on a
combination of manual annotations
and “AI for AI” models.
Real-Time Monitoring
Get notified about any deviations,
drifts, or anomalies in the data that
would otherwise be 100%
unstructured.
LLM Gateway Coming Soon
Safeguard your LLM model from
generating toxic and harmful
responses in real time.
Understand and Debug Your LLM App As If
You’re Working With Tabular Data
LLM EvaluationÂ
Deepchecks LLM Evaluation module focuses on the pre-deployment phase, from the first version of your application all the way through version comparison and internal experiments.
Thoroughly test your LLM model characteristics, performance metrics, and potential pitfalls — based both on manual annotations and on properties calculated by Deepchecks’ engine. This includes analysis of everything from the content and style to any potential red flags.
Analysis
LLM Monitoring
Ensure optimal performance, identify drift, and simplify complying with AI regulations and internal policies.
Apply rigorous checks to ensure your LLMs consistently deliver optimal performance.
LLM Gateway Coming Soon
Safeguard your models with our LLM Gateway, a real-time barrier against any harmful outputs, like hallucinations. The LLM Gateway scans the inputs and outputs in real-time, enabling blocking of harmful content as well as re-routing specific inputs to another model or script when certain conditions are met.
Integrations
Featured Content
Brain John Aboze
Philip Tannor