Gentrace

What is Gentrace?

Gentrace is a platform for evaluating and monitoring generative AI models across three dimensions: output quality, speed, and cost. It combines human judgment, AI-based evaluation, and heuristics to automate much of the grading process, reducing the need for manual review.

Because evaluation runs continuously, you can quickly spot regressions or hallucinations — cases where a model’s performance degrades or it starts producing fabricated output.

A key feature is Observe, which provides real-time monitoring of models in production. It tracks speed and cost, lets you inspect specific inputs, outputs, and evaluator scores for each generation, and renders visual charts of pipeline runs so you can see how performance changes over time. Pipelines can also be traced step by step through each run.

Security is a priority: Gentrace uses enterprise-grade measures, including SOC 2 Type II controls, and has passed audits. Admin and user controls help organize your team and manage access, with more granular controls planned. Self-hosted data storage is also in development for additional control over your data.

Integration is handled through a Python SDK, making it straightforward to fit Gentrace into an existing setup.

Who created Gentrace?

Gentrace was built by a team focused specifically on evaluation and monitoring for generative AI, with the goal of assessing models on quality, speed, and production cost.

What is Gentrace used for?

• Evaluating generative models on quality, speed, and cost
• Automating grading of AI outputs instead of manual review
• Detecting regressions and hallucinations as they occur
• Monitoring models in production with real-time speed and cost tracking
• Analyzing inputs, outputs, and evaluator scores for each generation
• Visualizing and tracing pipeline runs to see performance trends over time
• Managing teams with admin and user access controls

Summary

Gentrace offers automated grading, real-time production monitoring via Observe, and enterprise-grade security (SOC 2 Type II), with a Python SDK for integration and team management tools. It is a practical option for teams that need to evaluate and monitor generative AI models in production.