Athina AI is a company building an evaluation and observability layer for teams developing applications with large language models. As organizations move LLM features into production, they need to answer two hard questions continuously: is the output actually good, and is it degrading over time? Athina is designed to answer both, giving developers tooling that spans early prototyping all the way to live production monitoring.
At the heart of Athina is a broad library of evaluators covering the dimensions that matter for real applications. For retrieval-augmented generation, it offers checks for context sufficiency, context relevance, and answer faithfulness or groundedness. For safety, it detects personally identifiable information and other sensitive content. For accuracy, it includes hallucination detection and correctness scoring, and it supports configurable LLM-as-a-judge evaluators that score responses against custom criteria. Teams can run these evaluators on development datasets to compare prompts and models, then continue running them against live traffic.
The observability side of Athina provides a dashboard for monitoring production AI systems. Teams can track operational metrics like cost, latency, and token usage alongside quality metrics over time, making it possible to spot regressions quickly and understand the impact of a model upgrade or prompt change. By unifying experimentation and production monitoring under a shared set of metrics, Athina helps teams maintain confidence in AI behavior after launch, not just before it.
Athina was founded in 2022 and is backed by Y Combinator. It has raised seed-stage funding of roughly $3M led by AIM-affiliated and YC-aligned investors, with additional participation from funds including Flourish and Scout. The platform targets developers and AI teams who want a practical, evaluator-rich workflow for shipping reliable LLM and RAG applications.