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README.md

@@ -374,7 +374,7 @@ Inspired by [awesome-python](https://github.com/vinta/awesome-python).
 * [Manifold](https://github.com/uber/manifold) - A model-agnostic visual debugging tool for machine learning.
 * [NannyML](https://github.com/NannyML/nannyml) - Algorithm capable of fully capturing the impact of data drift on performance.
 * [Netron](https://github.com/lutzroeder/netron) - Visualizer for neural network, deep learning, and machine learning models.
-* [Opik](https://github.com/comet-ml/opik) - Evaluate, test, and ship LLM applications with a suite of observability tools to calibrate language model outputs across your dev and production lifecycle.
+* [Opik](https://github.com/comet-ml/opik) - Evaluate, test, and ship LLM applications with a suite of observability tools.
 * [Phoenix](https://phoenix.arize.com) - MLOps in a Notebook for troubleshooting and fine-tuning generative LLM, CV, and tabular models.
 * [Radicalbit](https://github.com/radicalbit/radicalbit-ai-monitoring/) - The open source solution for monitoring your AI models in production.
 * [Superwise](https://www.superwise.ai) - Fully automated, enterprise-grade model observability in a self-service SaaS platform.