Gentrace
Automate LLM evaluation to improve AI product reliability
Target Audience
- AI engineering teams
- LLM product managers
- Machine learning engineers
- Technical leaders deploying AI features
Hashtags
Overview
Gentrace helps AI teams collaboratively test and optimize language models through automated evaluations. It provides tools to compare model versions, tune prompts, and monitor production performance in one platform. Teams can align technical and non-technical stakeholders to build more reliable LLM-powered applications.
Key Features
Collaborative Testing
Enable cross-team LLM evaluation through shared interfaces
Experiment Tracking
Compare prompt variations and model parameters systematically
Production Monitoring
Debug live RAG pipelines and agent performance issues
Custom Metrics
Create hybrid evaluations combining code, LLMs, and human input
Use Cases
Test LLM application versions before deployment
Tune retrieval systems and prompt configurations
Compare model performance across environments
Monitor production AI pipelines in real-time
Pros & Cons
Pros
- Collaborative interface for technical/non-technical teams
- Supports multimodal evaluation (code+LLM+human)
- Production environment monitoring capabilities
- Customizable metrics for specific use cases
Cons
- Steep learning curve for non-AI teams
- Enterprise pricing requires direct contact
- Limited pre-built templates for common scenarios
Frequently Asked Questions
Can non-engineers contribute to evaluations?
Yes, Gentrace provides UI tools for cross-functional team collaboration
Does it support human-in-the-loop evaluations?
Yes, combines automated LLM checks with human judgment inputs
Can we monitor production AI systems?
Yes, tracing features help debug live RAG pipelines and agents
Reviews for Gentrace
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