Athina AI

Athina AI is an AI engineering platform designed for developers and product teams building applications powered by large language models. Rather than focusing solely on prompt creation, the platform provides an end-to-end environment for developing, testing, evaluating, and monitoring AI features throughout their entire lifecycle. It enables organizations to improve the reliability of AI applications before and after deployment by combining prompt experimentation, automated evaluations, analytics, and production monitoring into a single collaborative workspace.

One of Athina's core capabilities is its evaluation framework, which supports more than 50 built-in evaluation metrics from providers such as Athina, OpenAI, Ragas, and Guardrails, while also allowing teams to create custom LLM-as-a-judge evaluations or Python-based evaluation functions. Developers can compare prompts, models, and retrieval strategies, identify regressions, and continuously measure response quality using datasets tailored to their own applications.

The platform also provides comprehensive observability for production AI systems. Teams can log every inference, monitor latency, token usage, costs, user feedback, and model performance, while segmenting analytics by customer, environment, model, or application. These insights help organizations quickly identify quality issues, optimize prompts, and make data-driven improvements to Retrieval-Augmented Generation (RAG) pipelines and other AI workflows. Collaboration tools allow engineers, product managers, and AI specialists to work together on prompts, datasets, evaluations, and experiments from a shared interface.

Athina offers a free Starter plan with up to 10,000 logs per month, advanced analytics, unlimited prompts, and prompt comparison tools. Paid Pro and Enterprise plans provide unlimited logs, evaluations, datasets, team collaboration, APIs, self-hosting options, advanced access controls, and enterprise support. Overall, Athina AI provides a comprehensive platform for building more reliable, measurable, and production-ready AI applications.