Traceloop turns evals and monitors into a continuous feedback loop - so every release gets better
OpenLLMetry is perceived to have a very positive reputation, particularly noted for its accessible AI capabilities and ease of use. Users appreciate its open-source nature, which allows for extensive customization and community-driven improvements. While there are limited explicit complaints in the social mentions, the lack of detailed reviews could suggest a nascent user base or limited adoption. Pricing sentiment is not discernible from the available information, indicating it may either be competitive or not a focal point of discussion amongst users.
Mentions (30d)
0
Reviews
0
Platforms
1
GitHub Stars
6,958
905 forks
OpenLLMetry is perceived to have a very positive reputation, particularly noted for its accessible AI capabilities and ease of use. Users appreciate its open-source nature, which allows for extensive customization and community-driven improvements. While there are limited explicit complaints in the social mentions, the lack of detailed reviews could suggest a nascent user base or limited adoption. Pricing sentiment is not discernible from the available information, indicating it may either be competitive or not a focal point of discussion amongst users.
Features
Use Cases
Industry
information technology & services
Employees
3
Funding Stage
Merger / Acquisition
Total Funding
$66.7M
197
GitHub followers
24
GitHub repos
6,958
GitHub stars
20
npm packages
Pricing found: $0 / mo
Repository Audit Available
Deep analysis of traceloop/openllmetry — architecture, costs, security, dependencies & more
Yes, OpenLLMetry offers a free tier. Pricing found: $0 / mo
Key features include: Start tracking in seconds, Run quality checks with zero setup, Define quality on your terms, Make quality part of the pipeline, Open standards at the core, Works with every stack, Compatible with the tools you actually use, Product.
OpenLLMetry is commonly used for: Real-time monitoring of LLM performance in production environments, Automated quality checks for machine learning models, Debugging and troubleshooting of black box models, Integration of observability tools into existing ML pipelines, Customizable quality metrics for diverse ML applications, Seamless collaboration between data scientists and DevOps teams.
OpenLLMetry integrates with: TensorFlow, PyTorch, Kubernetes, Apache Kafka, Prometheus, Grafana, Jupyter Notebooks, Slack, GitHub, AWS S3.
OpenLLMetry has a public GitHub repository with 6,958 stars.
