Meet the Team
Sriniwas Gedella
Founder & CEO
Ankit Srinivas
Co-Founder & GTM Engineer
Jason Egnal
Advisor
Distributed software systems — and the AI agents increasingly operating within them — require a new class of infrastructure: a governance layer that evaluates whether a change is safe to execute before it commits to production.
Legible is building that layer. Not a better observability tool. Not a more intelligent alerting system. The missing control primitive — the enforcement layer that sits between deployment execution and production reality.
Detectable by existing tools. A metric spikes, an alert fires, an on-call engineer gets paged. The failure class observability was designed to catch.
Deployment-induced drift. Cross-service dependency breaks. Blast radius expansion. Everything appears healthy. Dashboards are green. The incident is already propagating.
A governance layer that evaluates whether a change is safe to execute — using live production evidence — before it commits. Not detection after the fact. Prevention before execution.
Every observability platform built over the last fifteen years was designed around a shared assumption: if execution completes without an error, it is correct. That assumption is no longer valid. 64% of production outages trace directly to changes that passed every check.
Testing validates code logic. Observability shows what happened after the fact. Feature flags control who sees a change. None of them answer the question that matters at the moment of deployment.
Given what's happening in production right now — is this change safe to execute?
That's the question no existing tool answers. Legible is building the layer that does.
Git governs code · Kubernetes governs infrastructure
Legible governs deployment safety
Filed in early 2026, the portfolio occupies the specific technical territory between post-hoc observability, static policy evaluation, and process mining. Each application covers a layer of the governance stack. Replicating any single layer without the full stack produces an incomplete and commercially unviable result.
Non-provisional filing deadline: February 2027 · Two-track prosecution strategy
Developers using AI coding tools interact with 47% more pull requests per day (DORA 2025). Change failure rates are rising, not falling. More changes are reaching production faster with less safety review of their production impact.
Large enterprises run 15,000+ APIs. A single page render touches 100+ services. The dependency graph compounds: one change cascades in ways no individual team can predict from their own system view alone.
AI agents are now writing code, triggering deployments, and modifying production configuration without human sign-off. The production-aware safety gate that answers "is this action safe?" doesn't yet exist at scale.
We're onboarding two to three design partners now. Deployment begins with read-only observation — no code changes, no pipeline modifications.