An AI-native quality engineering platform replacing mobile QA departments — and the missing feedback loop for every AI coding agent that ships mobile code.
We're replacing manual mobile testing with an AI-native quality engineering platform — built specifically for the era where 41% of code is written by agents and tested by no one.
Three forces are converging — and the first AI-native mobile QA platform to capture mid-market mind share will define the category.
Every Claude Code, Cursor, and Codex deployment is a flying blind iteration. The Agent Feedback API is a $500M opportunity — designed into Aucert's architecture from Day 1.
More devices, more OS versions, more form factors per quarter. Emulator-first economics with AI Device Twin overlay solves what device-cloud incumbents structurally cannot.
Firebase App Testing Agent: Gemini-powered, free, in preview. Currently Android-only. The window closes when Google extends to iOS — likely 12–24 months. Speed is the only defense.
Each layer is independently optimized, MCP-standardized for inter-layer communication, and decoupled enough to swap models without re-engineering the system.
A relational map of each customer's app — Code ASTs, runtime telemetry, historical bug patterns, UI component graph. "Truth is in the code, not the docs."
Predictive models simulating real-device behavior from emulator tests. Emulator-first economics. Real-device accuracy.
The Agent Feedback API positions Aucert as the quality gate for AI coding agents — Claude Code, Cursor, Codex. We design for it from Day 1. We build it after PMF.
Combined opportunity expands the addressable market 3–5x. Exit multiples shift from QA/DevOps (5–8x) to AI platforms (15–30x).
Good API hygiene. Costs nothing extra. Serves both humans and agents. Designed for the future. Doesn't depend on it.
Built at Month 12–18 only after 10+ paying customers and >80% accuracy proof. Discipline is the moat. Premature scope creep is the named risk.
200–2,000 employees. Fintech, e-commerce, health-tech. Mobile is core revenue, not adjunct. Target ACV $120–300K.
BFSI = 28.3% of mobile testing spend. Mobile banking failures = direct monetary loss + regulatory fines. Non-discretionary budget. Vivek's PhonePe pedigree opens doors cold outreach cannot.
$15–30M ARR
75–150 customers. ~0.2% of SAM.
| Player | Threat Level | AI-native | Knowledge Graph | Device Twin | Agent API | Cross-customer learning |
|---|---|---|---|---|---|---|
| Aucert | — | ● | ● | ● | ● | ● |
| BlinqIO | HIGH | ● | ○ | ○ | ○ | ○ |
| Firebase App Testing | EXISTENTIAL | ● | ◐ | ○ | ○ | ◐ |
| BrowserStack | MED | ○ | ○ | ○ | ○ | ○ |
| TestMu / Sofy / Apptest | MED | ◐ | ○ | ○ | ○ | ○ |
Each layer requires the previous one to validate. We tell investors what's earned versus what's earned-with-execution. Composite grade today: B+. Path to A- in 18 months.
Three sequential phases. Founder-led sales powered by the PhonePe story. Land at $120–180K ACV. Expand to $240–480K through capability modules — the SentinelOne / CrowdStrike playbook applied to QA.
Both technical founders have managed mobile QA at scale. Bay Area + India distribution. Expert syndicate team grade: A.
14 years mobile development. PhonePe founding team, led Mobile QA at $12B fintech with 500M+ users. Flipkart early mobile team. WhatsApp billion-user-scale engineering. Architect-track since.
14 years engineering. PayPal enterprise fintech backend at global scale. Multiplier B2B SaaS — oversaw QA team. Director-level engineering leadership. Polyglot: JVM & Go.
beans.ai COO ($24M raised, 500+ enterprise customers including FedEx, Verizon, Domino's). McKinsey consulting background. MBA. B2B sales-cycle management and operational scaling.
Validate product-market fit with 5–10 design partners. Achieve SOC 2 Type I. Build the core platform through Month 12.
Build the ugliest possible thing that proves the Knowledge Graph makes tests better than a prompt. Six weeks. One framework. One emulator. If it works, customers will forgive the ugliness.