What can Humanloop evaluate?

Teams can evaluate prompts and AI application outputs with code evaluators, LLM-as-a-judge evaluators, human review, datasets, and custom evaluation workflows.

Does Humanloop support CI/CD?

Yes. Humanloop supports evaluation workflows in CI/CD so teams can detect regressions and compare changes before deploying AI features.

Humanloop offers a free trial with 2 members, 50 evaluation runs, and 10,000 logs per month. Production enterprise pricing is custom.

Who is Humanloop for?

It is built for engineers, product managers, and domain experts responsible for evaluating, improving, and monitoring production AI systems.

Humanloop

Name: Humanloop
Brand: Humanloop

LLM evaluation, prompt management, and observability platform for production AI teams.

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What is Humanloop?

TL;DR

Humanloop is an LLM evaluation, prompt management, and observability platform that helps teams test model behavior, compare prompts, monitor production AI, and prevent quality regressions across applications.

Run automated, human, and LLM-as-a-judge evaluations against versioned datasets to measure AI quality before release.
Manage prompts, model experiments, deployments, logs, traces, alerts, and user feedback across the AI application lifecycle.
Connect major model providers and integrate evaluations into CI/CD to catch regressions before production changes ship.

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About

Humanloop is an LLM evaluation, prompt management, and observability platform for teams building AI applications in production. It gives engineers and product teams a shared environment to develop prompts, evaluate model behavior, monitor AI systems, and improve reliability before and after deployment. Teams can manage and version prompts, connect multiple model providers, build datasets, and run offline or online evaluations using code evaluators, LLM-as-a-judge evaluators, and human review. Humanloop also supports evaluation reports, CI/CD integration, experiment comparison, feedback collection, logging, tracing, alerts, and production monitoring. The platform connects the development and production sides of AI engineering. Developers can run evaluations from code or the UI, compare model and prompt changes against versioned datasets, detect regressions before deployment, and inspect production logs and user feedback. Humanloop supports major providers including OpenAI, Anthropic, Google, Azure, Cohere, AWS Bedrock, and custom models through its APIs. Humanloop is particularly useful for founders, AI product teams, engineers, and domain experts who need a repeatable evaluation workflow rather than ad-hoc prompt testing. It is a strong fit for customer-facing LLM applications where quality, safety, observability, and regression testing matter. Enterprise capabilities include SSO, RBAC, VPC deployment options, compliance support, dedicated environments, and enterprise support.

Use Cases

Evaluate AI quality

Benchmark prompts and model outputs with automated, human, and LLM-as-a-judge evaluators before shipping changes to production.

Prevent AI regressions

Run versioned datasets and evaluations in CI/CD to catch quality, safety, or performance regressions before deployment.

Monitor production AI

Inspect logs, traces, alerts, end-user feedback, and evaluation results to understand AI behavior after deployment.

Manage prompts centrally

Create, version, test, and deploy prompts across engineering and product teams while tying changes to evaluation results.

Key Features

Prompt management and versioning across AI applications
Code, human, and LLM-as-a-judge evaluations
Datasets, experiments, and evaluation reports
Production logs, traces, alerts, and feedback

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