Brittle Selenium locators are a leading cause of flakiness in UI test suites, forcing developers and QA teams to spend hours each week triaging false failures and slowing the shift-left testing movement. This problem is acute across roughly 500,000 software teams—particularly enterprise and midmarket engineering orgs that already pay around $12K ACV for test automation tooling—yielding a total addressable market of about $6.0B. You could build a self‑healing locator platform that combines resilient selector generation, DOM structural modeling, and AI-driven embeddings to match and repair locators automatically, surface high‑confidence fixes as automated PRs, and aggregate failure telemetry across cloud CI pipelines to prioritize robust repairs. Cloud CI adoption and advances in model inference make robust element matching and cross-customer learning feasible today, which is reflected in a market score of 88/100 and revenue potential of 92/100. Offering privacy-preserving telemetry and on‑prem options will be important to win enterprise customers in this window of opportunity. To stand out, focus on delivering measurable reductions in locator-related triage time, seamless integration with Selenium/Playwright and major CI systems, and conservative repair heuristics to avoid introducing new test regressions; these are achievable but technically nontrivial. Competition is medium and fragmented, so success will hinge on execution, demonstrable ROI (fewer flaky CI runs, lower MTTR), and strong privacy and security guarantees rather than bold claims.