The memory layer your AI agents are missing.
TestRelic turns every test run into shared application context for Cursor, Claude Code, Copilot, and Codex — so the whole team ships at senior-IC speed.
Our Mission
Every engineering team is shipping with AI now. Most are losing the same battle every day: their AI knows JavaScript and Python — it doesn't know their app. Which flows are flaky, which selectors changed last sprint, which user paths matter. That knowledge lives in one senior engineer's head and gets re-explained, badly, in every new chat. TestRelic exists so it doesn't have to.
How We Started
TestRelic started as a test-observability platform — dashboards for Playwright, Appium, and Maestro. Then we watched our own teams use Cursor and Claude Code and realized: the same data we were surfacing for humans was the highest-signal context an AI coding agent could possibly read. Tests describe how the app actually behaves. Failures describe what's actually fragile. Run history describes what's actually been fixed.
Generic memory products (Mem0, Zep, Redis Context Engine) store conversations. Augment indexes static code. Neither has the substrate we have: real runtime behavior of your app under test. So we built the MCP server. Then the org-scoped memory model. Then we rewrote the company around it. TestRelic is now the test-derived memory layer for every engineer's AI agent — composable with the rest of the context-engineering stack.
Founder
Srivishnu Ayyagari
Founder, TestRelic
Srivishnu was a founding product manager at TestMu AI (LambdaTest), where he built automation testing across web, mobile, and CI — plus visual regression and AI insights — for teams shipping quality at scale.
Later, at Qyrus, he led product and spent years deep in the no-code / low-code testing market, getting manual testers productive without writing a line of code. That's where the conviction behind TestRelic took shape: the hard part was never authoring tests — it's the context locked inside them.
He started TestRelic to turn that context into shared memory every engineer's AI agent can read — so an entire team works at the level of its most senior IC, not the level of a blank chat.
What We Stand For
Substrate Over Surface
Anyone can build another dashboard. The hard part is the substrate — what's underneath. We invest in the memory layer first, then surface it to humans and to AI agents in equal measure.
Team Intelligence, Not Hero Intelligence
An engineering org should not bottleneck on one IC's tribal knowledge. We build so every teammate's AI agent gets the same context as the senior engineer who's been there longest.
Compose, Don't Compete
Mem0, Zep, Augment, Redis Context Engine — they own parts of the context-engineering stack. TestRelic owns runtime behavior. We ship MCP, AGPL-3.0, and open APIs so we slot in beside them, not on top.