Humanloop

Categories: Coding & Developer Tools, Data Analysis, Productivity | Pricing: Freemium | Official Website ↗

Humanloop is an LLM Evals Platform for enterprises to develop, evaluate, and ship trustworthy LLM-powered applications.

Humanloop is an enterprise platform designed to help teams build robust AI features by focusing on evaluation, prompt management, and observability of AI systems. It provides tools for prompt engineering, collaborative workspaces, multi-LLM playgrounds, and version control for prompts and deployments. The platform supports both UI-first and code-first workflows, enabling collaboration between engineers, product managers, and domain experts. Key functionalities include comprehensive evaluation tools with reports, integration into CI/CD, dataset management, and various evaluators (offline, online, UI, code, and AI as judge). It also offers robust security features like VPC deployment, SOC-2 Type 2 compliance, custom SSO, and dedicated support. Observability features include online monitoring, tracing, alerting, and end-user feedback logging to continuously improve AI systems in production. The Humanloop team has recently joined Anthropic.

Key Features

Prompt Engineering
Collaborative Workspace
Multi-LLM Playground
Prompt Management
Function Calling
Tagged Deployments
Versioning and Tracking
Feedback & Corrections

Pros

Provides a comprehensive platform for LLM development, evaluation, and deployment.
Enables collaboration between technical and non-technical team members.
Offers robust evaluation tools, including AI and human review.
Supports various LLM providers and custom models via API/SDK.
Includes enterprise-grade security and compliance features like SOC-2 and HIPAA.

Cons

The Humanloop platform is being sunsetted as the team joins Anthropic.
Pricing for enterprise features requires direct contact with sales.
Users pay for LLM API usage separately from Humanloop.
Free plan has limited members, eval runs, and logs.
Requires users to transition off the platform due to the acquisition.

Use Cases

Developing and iterating on LLM applications
Evaluating the performance of AI systems
Managing and versioning prompts
Monitoring AI systems in production
Ensuring security and compliance for AI deployments

Best For

Enterprises building LLM-powered applications
Product teams developing AI features
Engineers implementing AI evaluations and monitoring
Product Managers and domain experts involved in prompt engineering

Integrations: CI/CD systems

Platforms: Web

Watch demo on YouTube ↗

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