Evaluation for LLM-Based Apps | Deepchecks

Release high-quality LLM apps quickly without compromising on testing. Never be held back by the complex nature of LLM interactions.

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LLM Evaluation

Define, Measure, and Validate AI Progress

Release high-quality LLM apps quickly without compromising on testing. Never be held back by the complex and

subjective nature of LLM interactions.

Leading AI Teams Love & Trust Deepchecks

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Evaluation is Complex

LLM applications have no test set, causing a measurement problem. Without standardized

performance metrics, credible auto-scoring, and streamlined version comparisons, every evaluation

task becomes "a project"- slowing down innovation and increasing risk.

A small change in the answer might change the meaning of the answer completely.

Organizations face growing challenges in evaluating LLM performance

consistently, scaling their LLM apps to production, and making reliable, data-

driven decisions. Deepchecks' platform streamlines a process of configuring

auto-scoring and applying it to your LLM-based app during dev, CI/CD and

production.

Why Choose Deepchecks

Generative AI produces subjective results. Knowing whether a generated text is good usually requires

manual labor by a subject matter expert.

Compare versions of prompts, models, agents, & AI systems

Set up an auto-scoring pipeline, addressing nuanced constraints

Generate datasets and create LLM judges within minutest

Leverage auto-scoring for annotations and data slicing & dicingst

Test LLM apps within the CI/CD and monitor them in production

0x

improvement of “time to production” for a new LLM app

0%

decrease in hallucinations and low-quality responses

0x

# of versions compared before choosing the winner

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SOTA small language models & Agentic workflows

Swarm of Evaluation Agents

The algorithmic backbone of Deepchecks is a set of small language models (SLMs) & multi-step NLP pipelines, that work together as a swarm using Mixture of Experts (MoE) techniques to simulate an intelligent, human, annotator.

Superior AccuracyCustomizable LLM EvaluatorsEvaluate Agents with Agents

Superior Accuracy

Unparalleled accuracy for groundedness, retrieval relevance, and more (backed up by studies that can be sent upon request).

Customizable LLM Evaluators

Alongside the SLMs, Deepchecks enables the interactive, no-code creation of evaluators using LLMs and a Chain-of-Thought.

Evaluate Agents with Agents

Each evaluation agent can assess a different span, thus enabling the swarm to evaluate anything from a simple RAG to a complex agentic workflow.

End-to-End Platform

Deepchecks LLM Evaluation Platform

The term "LLM Evaluation" is often associated with techniques or open-source projects that focus on LLM-as-a-judge techniques. Teams that leverage these are still miles away from actually solving the problem, typically still needing large DIY projects and arriving at evaluation infra that lacks accuracy, consistency, future-proofing and the ability to transfer ownership non-coders. At Deepchecks, "LLM Evaluation" means an all-inclusive platform, that actually solves the problem.