LLMTest – The pytest for LLMs with 22 built-in assertions
Pytest syntax for LLM testing avoids LLM-judge cost, but feature parity vs. LangSmith and Braintrust unproven.

Catches silent UI regressions that Sentry and RUM dashboards completely miss.
Frontend developers, QA engineers, and Engineering managers
Sentry · Datadog RUM · LogRocket
Pytest syntax for LLM testing avoids LLM-judge cost, but feature parity vs. LangSmith and Braintrust unproven.
Turns dusty E2E tests into marketing videos—solves the demo recording grind.
Records flows and auto-fixes failing tests until green.
Agentic test runtime builds execution memory to heal flaky tests automatically.
I built Attest because every team I've seen building AI agents ends up writing the same ad-hoc pytest scaffolding — checking if the right tools were called, if
Natural-language -> E2E tests plus a visual desktop app, cloud sync and an npm-installable CLI is a pragmatic combo that will appeal to teams tired of brittle scripts. Usability-focused reporting and a recorder-ish desktop experience are the clearest differentiators here; what I want to see next is concrete evidence about cross-browser reliability and how the AI handles flakiness and changing selectors.