Aucert
Aucert runs AI agents that autonomously explore, test, and verify mobile app builds against a team's own standards
The Problem
Mobile-first teams shipping high-consequence apps currently rely on manual QA review to check every build against design, accessibility, policy, and security standards. This checking by hand consumes significant engineer and QA time per release and still leaves gaps, since no single human reviewer can cover every dimension (design, accessibility, Play and App Store policy, validation, security) on every build. The page illustrates this cost with a worked example: 25 mobile engineers spending 4 validation hours per engineer per release across 4 releases a month, plus 3 blocking incidents a quarter, translating into hundreds of engineering days and significant recovered value if eliminated. As AI codegen increases the volume of builds, this manual bottleneck is described as being overwhelmed from the inside.
The Solution
Aucert deploys a bench of expert AI agents, each focused on a domain such as design (Genie), accessibility (Iris), validation (Vera), Google Play policy (Pax), Apple App Store policy (Ash), and build analysis (Dax), coordinated by a steward agent (Sage). The system works in three steps: it explores the app like a user would to map every screen and flow and keep that map current (product intelligence); it captures a team's standards as explicit expectations, sourced from agents, written policies, and humans, with experts suggesting additions and nothing enforced without approval (expectations); and it then validates every build against those expectations, generating tests and producing a pass/fail status report with a release gate that can be overridden with a reason or held (validate and enforce). It supports Android, iOS, Kotlin Multiplatform, and React Native today, with Flutter, Web, macOS, and Windows coming soon. Teams can try it via a guided tour on a sample app, request a free first scan by submitting an app store link, or use an ROI calculator to estimate validation cost savings.
Why Now?
The founders describe watching AI-driven code generation overwhelm manual QA pipelines, framing Aucert as the automated layer needed to keep pace with that increased build volume.
