Imagine you’re creating an AI tool that answers questions, writes content, or helps users navigate complex info. You want it to be accurate, consistent, and easy to improve, but managing prompts, testing ideas, and keeping everything working smoothly can feel like juggling chainsaws.
So here comes Agenta!
What is Agenta?
Agenta is a smart workspace for building reliable AI tools. Test prompts, try 50+ models, track changes like code, and collaborate safely. See real-time results, avoid chaos, and ship smarter AI apps, fast. Perfect for teams, writers, and experts who want powerful, trustworthy AI without the hassle.
Agenta makes it simple, think of it as a clean, intuitive workspace where:
- You can test different prompt ideas side by side, like comparing two versions of a question to see which one gives better answers.
- You can try out 50+ AI models, or even plug in your own, no coding needed.
- You can save, organize, and track changes to your prompts, just like version control for code, but for AI logic.
- Teams (and even non-tech experts!) can collaborate safely on improving how the AI works, no more “I changed something and now it broke.”
- You get real-time feedback on how well your AI is performing, so you know what’s working and what needs tweaking.
It’s like giving your AI team a dedicated command center: organized, reliable, and built for real-world use, not just experiments.
Agenta isn’t just for engineers. It’s for product teams, writers, researchers, and anyone who wants to build smarter AI tools, fast, confidently, and together.
Perfect for teams tired of trial-and-error chaos. Agenta brings order, clarity, and teamwork to the world of LLMs.
Use Cases
- Prompt Engineering & Optimization: iteratively testing and refining prompts to improve response quality before deployment.
- Regression Testing: Ensuring that changes to prompts or models do not degrade performance by running automated evaluations against established test sets.
- Production Monitoring: Tracking the real-time cost, latency, and errors of live LLM applications to ensure reliability.
- Collaborative App Development: Enabling non-technical domain experts to tweak prompts and configurations while engineers handle the underlying code.
- Model Comparison: systematically comparing the output of different LLM models (e.g., GPT-4 vs. Claude 3 vs. Llama 3) to choose the best one for a specific task.
Features List
- Prompt Management & Engineering:
- Interactive LLM Playground: Compare different prompts side-by-side against test cases.
- Version Control: Manage versions of prompts and configurations with branching and environment support.
- Multi-Model Support: Experiment with over 50 LLM models or integrate custom models.
- Collaborative Workflow: Allows Subject Matter Experts (SMEs) to collaborate on prompts and complex configurations without breaking production code.
- LLM Evaluation:
- Flexible Testsets: Create test cases from production data, playground experiments, or uploaded CSV files.
- Automated & Human Evaluation: Supports “LLM-as-a-judge,” 20+ pre-built evaluators, and custom evaluators.
- Human Feedback: Interface for collecting expert annotations and human feedback.
- Programmatic & UI Access: Run evaluations via a visual interface (for SMEs) or API (for engineers).
- LLM Observability:
- Cost & Performance Tracking: Monitor latency, spending, and usage patterns.
- LLM Tracing: Debug complex workflows using detailed traces.
- Open Standards: Native OpenTelemetry support compatible with OpenLLMetry and OpenInference.
- Integrations: Pre-built integrations for major models and frameworks.
In short: Agenta turns AI experimentation into real, production-ready apps — with less stress and more results.
License
MIT License
