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---
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headline: Roadmap | Opik Documentation
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og:description: Explore Opik's evolving roadmap and contribute ideas to enhance our
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open-source project as we develop new features and improve functionality.
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og:site_name: Opik Documentation
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og:title: Roadmap for Opik - Open-Source Development Insights
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title: Roadmap
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canonical-url: https://www.comet.com/docs/opik/
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---
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Opik is [Open-Source](https://github.com/comet-ml/opik) and is under very active development. We use the feedback from the Opik community to drive the roadmap, this is very much a living document that will change as we release new features and learn about new ways to improve the product.
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<Tip>
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If you have any ideas or suggestions for the roadmap, you can create a [new Feature Request issue](https://github.com/comet-ml/opik/issues/new/choose) in the Opik Github repo.
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</Tip>
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## 🚀 What have we recently launched?
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Curious about our latest updates? Explore everything we’ve shipped in our [changelog](/v1/changelog).
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## 🛠️ What are we currently working on?
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We are currently working on both improving existing features and developing new features:
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**Agents & Optimization**:
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- New capabilities for agent and prompt optimization
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**Strategic work**:
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- Advanced multi-modal support
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- New Webhook Alerts System
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**Developer Experience**:
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- JS/TS SDK and REST API improved support
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**User Experience**:
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- Improved onboarding experience
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- Updated docs and mobile experience
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## 🧭 What is planned next?
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**Agents & Optimization**:
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- Simplified optimization workflow: the new Optimization Studio.
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- Build better AIs: advanced agent optimization powered by new algorithms.
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- Multi-objective optimizer with support for latency and cost
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**User Experience**:
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- Enhanced table support across the product: smarter sorting, flexible filtering, seamless exporting, and powerful bulk actions for effortless data management.
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## 🔭 What's coming later?
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Looking a bit further ahead, we plan to invest in deeper optimization, collaboration and observability tooling:
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**Advanced evaluation**:
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- Smarter AI performance assessment: Reinforcement Learning from Human Feedback for LLM-as-a-Judge metrics.
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**Closing the improvement loop**:
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- Automatically optimize agents across the entire lifecycle by leveraging production data and key performance metrics
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**Projects & Dataset improvements**:
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- Dataset editing and versioning
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- Support public and private projects
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- Introduce evaluation features in the Opik playground
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**Monitoring & Analytics**:
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- Introduce dashboarding features
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## 💬 Provide your feedback
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We rely on your feedback to shape the roadmap and decide which features to prioritize next. You can upvote existing ideas or even
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add your own on [Github Issues](https://github.com/comet-ml/opik/issues/).
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*Last updated: Q4 2025* |