Iterate Quickly
While Maintaining Control
complex and subjective nature of LLM interactions.
Evaluation is Complex
manual labor by a subject matter expert.
A small change in the answer might change the meaning of the answer completely.
Evaluate quality & compliance
If you’re working on an LLM app, you probably
know that you can’t release it without addressing
countless constraints and edge-cases.
Hallucinations, incorrect answers, bias, deviation
from policy, harmful content and more need to be
detected, explored and mitigated before and
after your app is live.
Deepchecks does it systematically.
Golden Set
A proper Golden Set (The equivalent of a test set for GenAI)
will have at least a hundred examples. Manual annotations
typically take 2-5 minutes per sample, and require waiting,
reviewing, correcting and sometimes hiring.
Good luck with doing this for every experiment or version
candidate!
Deepchecks’ solution enables you to automate the
evaluation process, getting “estimated annotations” that
you only override when you have to.
Open Core Product
product is widely tested and robust.
Open Source ML Testing
solution for comprehensively validating your
machine learning models and data with minimal
effort, in both the research and the production
phases.
![Open Source ML Testing](https://cdn.statically.io/img/deepchecks.com/wp-content/uploads/2024/02/img-opensource-ml-testing.png)
![ML Monitoring](https://cdn.statically.io/img/deepchecks.com/wp-content/uploads/2024/02/img-ml-monitoring.png)
ML Monitoring
Model performance is a critical component of a
healthy application. To maximize your business
performance, ML and IT teams need to
continuously know the status of their model.Deepchecks Monitoring makes sure that your
models and data are validated continuously.
LLMOps.Space
practitioners. The community focuses on LLMOps-related content, discussions, and
events. Join thousands of practitioners on our Discord.