Leading AI Teams Love & Trust Deepchecks
Integrated Experience to
Define, Measure, and Validate AI Progress
AWS Managed Service
On-Prem: 100% Data Locality
Best-in-Breed LLMOps Stack
One Click Away
Streamline LLM evaluation with clear, actionable insights to optimize your LLM projects. Effortlessly assess and refine your LLM applications, identify key areas of success and opportunities for improvement, and prepare your LLM applications for production.
Meets Your Enterprise
Security Needs
Ensure enterprise security with built-in governance throughout the entire LLM application lifecycle. Control access to the right data, models, and development artifacts by the right user for the right purpose.
Seamless Experience
Deepchecks' seamless integration with SageMaker AI, a part of the SageMaker Unified Studio, ensures a flawless experience across the entire LLM lifecycle – from proof of concept and beta releases to production monitoring.
Evaluate and Monitor
Your End-to-End LLM Workflow
Compare Versions of Your LLM Apps
- Experiment with different prompts, models, RAG setup, routing mechanisms, or any other parameters.
- Get a high-level overview of the performance differences of different pipelines.
- Find the key differences between each version.
Build, Expand, and Explore Your Evaluation Set
The Evaluation Set is like the “test set” from classic ML, adapted to benchmark custom LLM workflows.
- Generate, version, and expand evaluation sets, each designed for a specific LLM workflow.
- Explore your evaluation set to learn how you can improve the accuracy.
- Create and leverage ground truth.
Use Cases
Evaluate the quality and relevance of generated text, ensuring that outputs are coherent, contextually appropriate, and free of biases.
Featured Content
Yaron Friedman
Philip TannorDefine, Measure, and Validate
AI Progress
