Provides a platform for enterprises to develop, evaluate, and optimize large language models (LLMs) through version-controlled prompt management, automated and human-in-the-loop evaluations, and real-time observability tools. It addresses the limitations of traditional software development by enabling iterative, data-driven AI workflows that align product, engineering, and domain expertise to ensure model performance and reduce deployment risks.
Funding
$2.7M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
GPRDSCFounders
Product
Problem
Developing and deploying large language models (LLMs) requires iterative refinement based on data and domain expertise, which is not well-supported by traditional, code-centric software development tools. Existing workflows often lack the necessary version control, evaluation, and observability capabilities to ensure model performance and mitigate deployment risks.
Solution
Humanloop provides an LLM evaluation platform that enables enterprises to develop, evaluate, and optimize AI models through data-driven workflows. The platform offers version-controlled prompt management, automated and human-in-the-loop evaluations, and real-time observability tools. It facilitates collaboration between product managers, engineers, and domain experts, allowing them to iterate on prompts, datasets, and evaluators in a unified environment. By integrating with CI/CD pipelines, Humanloop helps teams prevent regressions and deploy AI models with greater confidence.
Target Audience
The primary target audience includes AI product teams, specifically product managers, engineers, and domain experts involved in developing and deploying LLMs in enterprise settings.
Features
- Prompt editor for collaborative prompt engineering with version control
- Automated evaluations using both AI and code-based metrics
- Human-in-the-loop evaluation UI for subject matter expert feedback
- Integration with any AI provider, avoiding vendor lock-in
- CI/CD integration for continuous evaluation and regression prevention
- Real-time observability tools for monitoring model performance in production
- Alerting and guardrails to proactively identify and address issues
- Online evaluations to capture user feedback on live data
- Tracing and logging capabilities to replay outputs and debug RAG systems
- Role-Based Access Control (RBAC) and Single Sign-On (SSO) for secure access
- VPC deployment option and EU/US cloud hosting to meet data privacy requirements