Ashr is a comprehensive platform designed to assist teams in building, evaluating, and monitoring AI agents, ensuring they function correctly before deployment. It offers tools for offline evaluation, production observability, and real-time analytics, enabling developers to identify and rectify issues proactively.
Key Features and Functionality:
- Testing Platform: Allows for the generation of datasets, running agents against test scenarios offline, and comparing expected versus actual behavior.
- Observability: Provides tracing of agents' production behavior, including LLM calls, tool invocations, retrieval steps, latency, and errors.
- Python SDK: Offers a lightweight SDK with zero external dependencies, facilitating seamless integration into existing codebases.
- Voice Session Analysis: Supports real-time voice agents on LiveKit, with features like turn timelines, transcripts, per-stage cost and latency analysis, mixed-audio replay, and barge-in metrics.
Primary Value and Problem Solved:
Ashr addresses the challenges of ensuring AI agents operate correctly by providing a robust framework for testing and monitoring. By identifying and fixing failures before they reach end-users, Ashr enhances the reliability and performance of AI systems, reducing downtime and improving user satisfaction.
