Hamming

Simulation and evaluation platform for voice and chat AI agents.

Coval is an evaluation and monitoring platform for conversational AI agents, applying the simulation-driven testing rigor developed in self-driving to voice and chat. From a handful of test cases it generates thousands of realistic scenarios, runs them against an agent over text or live phone calls, and scores the results on built-in or custom metrics. In production it monitors and scores real calls so teams can catch regressions across millions of conversations.

Simulate, evaluate, and observe AI agents end-to-end.

An end-to-end platform for testing and monitoring AI agents across their lifecycle. It combines a prompt experimentation IDE, agent simulation across scenarios and personas, offline and online evaluations with custom metrics, and production observability with tracing and alerts. Aimed at teams shipping reliable agentic and RAG systems.

Open-source LLM observability, evaluation, and agent testing.

An open-source platform for monitoring, evaluating, and testing LLM and agent applications. LangWatch captures traces, runs evaluations and simulations, and surfaces quality and cost metrics in production. Offered as managed cloud or fully self-hosted for teams with strict data-residency needs.

The AI quality platform from the team behind DeepEval.

Confident AI is the hosted platform built on top of DeepEval, the open-source LLM evaluation framework. It adds dataset and test management, research-backed metrics, production tracing and monitoring, adversarial red teaming, and governance dashboards so teams can benchmark, observe, and safeguard LLM apps across the dev-to-prod loop. Python and TypeScript SDKs plug into CI and OpenTelemetry, with managed cloud and enterprise self-hosting.