Agenta
AI Infrastructure & MLOps
LLMOps platform for prompt management, LLM evaluation, and observability. Build, evaluate, and monitor production-grade LLM applications with collaborative prompt engineering. )
Agenta is an open-source LLMOps platform designed for building and managing production-grade large language model applications. The platform provides comprehensive tools for prompt management, LLM evaluation, and observability across the entire development lifecycle. The platform enables teams to collaboratively engineer and test prompts, evaluate LLM outputs systematically, and monitor application performance in production. Agenta supports debugging of complex LLM applications and offers visibility into how models behave in real-world scenarios. Agenta is primarily built for developers and data teams who need to iterate on LLM-powered applications efficiently. It addresses common challenges in LLM development, including prompt optimization, quality assurance through structured evaluation, and production monitoring. As an open-source project, Agenta allows organizations to deploy the platform on their own infrastructure, avoiding vendor lock-in while maintaining full control over their LLM workflows and data. The platform integrates into existing development workflows and supports collaborative work across engineering teams. The combination of prompt engineering tools, evaluation frameworks, and observability features distinguishes Agenta from single-purpose solutions, positioning it as a comprehensive platform for the full lifecycle of LLM application development and deployment.
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Run and deploy AI models with a cloud API
Hey HN! I'm Fabio and I built UltraContext, a simple context API for AI agents with automatic versioning. After two years building AI agents in production, I experienced firsthand how frustrating it is to manage context at scale. Storing messages, iterating system prompts, debugging behavior an
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