PRE-SEED · JUNE 2026

The AI-native Validation Platform for Mobile Apps.

Independent validation at every step from idea to release — whether it's hand-written or AI-generated.

(Au)tomated (Cert)ification.

Raising $3M · invest@aucert.ai · Vivek Soneja & Rajesh Kumar

Confidential & proprietary — prepared for the named recipient. Not for distribution or reproduction.

02 / 10 TEAM · FOUNDER–PROBLEM FIT

The team that's lived this problem.

Vivek Soneja
FOUNDER · CEO

Vivek Soneja

San Francisco Bay Area · MS CS, Georgia Tech
15+ years building mobile since Android Cupcake (2009)
WhatsApp Meta Flipkart PhonePe
  • Improved WhatsApp's Android app for billions of users, at Meta
  • Founding architect at PhonePe — first commit to 500M+ users; now a ~$15B company
  • Built Flipkart's apps from scratch on the original app team — India's largest e-commerce platform
  • Owned the mobile QA pipelines Aucert now automates — and watched AI codegen break them
Rajesh Kumar
FOUNDER · CTO

Rajesh Kumar

Bengaluru · University of Wisconsin-Whitewater
Holds a US patent for the exact QA problem we're solving
PayPal Multiplier
  • A decade in PayPal's core payments infrastructure — reliability at financial scale
  • Building Multiplier's 0→1 global payroll engine across 80+ countries
  • Built under finance-grade compliance regimes — the policy layer Aucert now encodes
  • Leading the shift to AI-driven quality — knows why AI alone isn't enough
01
Lived the bottleneck. Shipped at billions-scale through Apple & Google review — every rejection, hotfix, and 3 AM production fire.
02
Owned the pipeline. Built — and patented — the exact QA systems Aucert now automates.
03
Building the platform. Saw AI codegen overwhelm that pipeline from the inside — now building the validation layer that removes it for every mobile team.

"Which is why we know exactly what's about to break →"

03 / 10 PROBLEM
QA cycle 01 / 02

QA has always been the bottleneck.

Complex, manual, brittle — every release drags through a device matrix, store-policy checks, and a regression suite that snaps on every change.

Dev effort 5 days
QA-driven cycle 13 days
Total cycle 18 days
QA : Dev ratio 2.6×

Illustrative single-feature cycle for a typical mid-market mobile team · directional, from founder operating experience.

Built at AI speed. Shipped at QA speed.

AI tripled development velocity and never touched verification — so the bottleneck exploded from 2.6× to 6.5×, and the store gate now matters more than ever.

Dev (with AI) 2 days
QA (unchanged) 13 days
Total cycle 15 days
QA : Dev ratio 6.5×
NOW MANDATORY 2M+ Apple rejections · 1.75M Google blocks in 2025 — now AI-screened. The store gate is getting harder, not easier.
04 / 10 MARKET
Market size 01 / 02

$25B and growing.

Aucert sits where mobile testing, app-security testing, and the new AI-native testing wave converge — each a multi-billion market growing double digits. Why we sum adjacent markets, not the whole ~$50B QA market.

SizeWhat it isGrowth
TAM $25–30B Global spend to get a mobile app safely to production — quality + validation + security + compliance. Σ adjacent markets: mobile app testing ~$9B · app-security ~$10.7B · AI test automation ~$8.8B (net of overlap).[27] → ~$70B by 2030
SAM ~$10B Mobile-shipping orgs already buying validation & testing tooling — Aucert's direct buyer. Mobile application testing market.[28] 13–17% CAGR
SOM $1.15B Bottom-up from segment pricing × reachable accounts — Indie $150M + Mid $400M + Enterprise $600M. See the bottom-up panel. 5-yr · ~12% of SAM
A single mobile testing / security tool reaches multi-billion outcomes: BrowserStack $4B · $381M ARR[8] Snyk $7.4B · ~$326M ARR[26] Tricentis $4.5B · $425M ARR[29]

The bottom-up path to $1B+.

Indie / AI-native · WEDGE
Solo + 1–5 dev teams. Wedge segment.
500K × 20% × $1.5K
$150M
Mid-market · DESIGN PARTNERS
5–100 devs. Regulated or release-heavy.
100K × 20% × $20K
$400M
Enterprise · DESIGN PARTNERS
100+ devs · multi-app portfolio · cross-store compliance.
15K × 20% × $200K
$600M
5-yr SOM
$150M Indie + $400M Mid-market + $600M Enterprise — three motions, one validation layer.
$1.15B
Conservatively excluded: Wearables · CarPlay · Wear OS · tvOS · Fire TV (same store-gate, ~$100–200M additional). OEM marketplaces. Regulated-vertical premium (fintech / health / gov-tech buy compliance at 2–3× standard ACV).
05 / 10 SOLUTION
Validation system 01 / 02

We don't script tests. We understand your product.

Traditional QA scripts every workflow by hand — then rewrites them on every change. We invert it: learn the product, capture your expectations, and generate the tests. Three innovations make that compound.

01
Product Intelligence

We understand your product — and never stop learning.

The failures that matter hide in the long tail — not the happy path everyone tests. Only a deep, ever-evolving model reaches them.

↻ Deepens every run
02
Policy Library

Your product's expectations — encoded once, enforced for all.

"Never leak PII," store rules, new vulnerabilities — ~70% is shared across apps, covered day one. Learn once, deploy to every customer: a real network effect.

↻ Network effect across customers
03
Validation Governance

The governance layer QA never had.

Define an expectation once; enforce it across every product and workflow. Bugs caught at the spec — shift-left by construction.

↻ Define once, enforce everywhere

One validation system. Four pillars that compound.

Same use-case layer on top. Underneath: Intelligence, Tests, Policies, Execution — wired as one system. Every pillar feeds the next, and every pillar gets sharper with each run.

Extensible Use Case Layer + CUSTOM WORKFLOWS
01Discuss
02Specify
03Build
04Review
05Monitor
06Ship
AUCERT VALIDATION SYSTEM
Aucert Native Engines
  • Rover
  • App Analyzer
  • Run learnings
Integrations
  • GitHub
  • Notion
  • Slack
  • GDocs
  • Firebase
Shared Policies
  • Apple Review
  • Google Play
  • Cross-customer
  • Aucert Fintech
  • Aucert Ecommerce
Custom Policies
  • Corp rules
  • PII rules
  • Brand · fintech
01

Product Intelligence

Unified intelligence layer — app screens, components and workflows.

Compounds per customer
02

Tests

Generated from Intelligence × Policies — curated baseline + per-customer customizations.

Self-maintaining
03

Policies

Rule library — shared baseline + proprietary corp policies, both enforced.

Tracks new rules
04

Execution

80 / 15 / 5 model cascade + device farm runs the test set. Every run sharpens both Intelligence and Policies — the loop closes here.

Cheaper & faster every cycle
SHIFT LEFT

Validation starts at the spec — not after the build.

We hook into every step from Discuss to Ship — the live feedback loop for agentic development.

PRODUCT INTELLIGENCE

Define an expectation once. Enforced on every screen.

Apps fork into thousands of flows — we learn the product, not the scripts. "No sensitive data in screenshots" holds on login, checkout and KYC alike.

POLICIES

70–80% of your rulebook, day one.

Stop rebuilding the same expectations — a shared library ships the baseline and evolves with Apple, Google, fintech and commerce.

06 / 10 WHY NOW

Two paradigm shifts in the last six months.

AI AMPLIFIED THE PROBLEM AI ENABLED BUILDING A SOLUTION
  • AI writes the majority of new code
    Q2 2026Up from 41% a year ago · mobile no exception · human QA capacity unchanged
    >50% AI-gen
  • Mobile codegen exploded
    Nov 2025 →Rork raised $15M · Replit Mobile · Cursor Mobile — all ship unvalidated APKs
    85% MoM
  • App stores cracked down
    Nov 13 2025Apple 5.1.2(i) AI disclosure now live · Apple + Google combined: 3.7M blocks
    ~3.7M rejected
  • AI now grasps intent
    Apr 2026Reads screens, flows, and specs — then writes and maintains the test suite on its own.
    Self-maintaining
  • AI debugs failures on its own
    Q1 2026Reasons about each failure, designs unique repro steps, returns a verified bug — not a flaky log.
    Autonomous triage
  • Frontier reasoning at SaaS-tier cost
    Q2 2026Open-weight models + low-cost APIs + cascade to frontier when it matters.
    Cascade routing

"Impossible six months ago. Inevitable six months from now."

07 / 10 COMPETITION · MOAT
Three moats 01 / 02

Three moats. All compound.

SHARED INTELLIGENCE MOAT

Policy Library

Learn once, deploy to allCrowdStrike pattern

10K+ store, corp & regulatory policies, kept current — a regression caught in one app inoculates the rest. Why the shared library compounds across customers.

PRODUCT INTELLIGENCE MOAT

Product Intelligence

Non-Pareto coveragereaches the long tail

A living model of your product — deeper every run, catching edge cases no script reaches. Why leaving means starting from zero.

COST MOAT

Verification Cascade

80% / 15% / 5%Haiku · Sonnet · Opus

Most scans never touch a frontier model — the cascade keeps inference structurally cheap, with software-grade margins. Why a naive all-Opus wrapper can't compete.

STRUCTURAL MOAT

Maker can't be checker

A model can't credibly grade its own output — Cursor, Copilot, Apple and Google all generate; none can independently validate. We sit in the seat both sides accept. An edge for independent validation — and we're built for it.

Where we sit. Mobile validation, not mobile testing infrastructure.

A 2×2 of mobile-test players on two axes — scripted→agentic and point solution→validation platform. We're alone in the top-right — and most of the field sells infrastructure, not a verdict.

View detailed comparison table (11 players)
Player What they sell Key differentiator
BrowserStack $4B · $381M ARR Cross-browser + real-device cloud Infrastructure, not a release signal. You still write the tests. No compliance intelligence.
Sauce Labs $1B+ raised Selenium / Appium cloud Same — IaaS. Built pre-AI. Manual test authoring required.
HeadSpin $124M raised Global real-device mobile + web testing Device-farm depth without the verdict layer. No store-rule library, no AI-codegen-specific posture. Sells minutes, not pass/fail.
Kobiton $46M raised · Atlanta Mobile-only device cloud + AI scripting Mobile-first device farm + self-healing Appium scripts. Still scripts-first; no store-policy intelligence; no cross-customer intelligence.
Perfecto Perforce-owned Enterprise mobile-first test orchestration Legacy enterprise stack — heavy, slow, pre-AI codegen. Bought into Perforce; no AI-native cascade, no OSS surface for developer pull.
Maestro mobile.dev · OSS YAML-flow mobile UI testing (Appium replacement) Closest in spirit (mobile-only, OSS-first) — but a test-authoring framework, not a verdict service. Customers run Maestro plus Aucert.
mabl $77M raised · Vista, CRV, GV Low-code AI test automation Web-first; you still author flows. Self-healing tests ≠ compliance signal. No cross-store rule pack.
Applitools $57M raised · Battery, Sierra Visual AI regression testing Single layer (visual) of the five we cover. Plugs in alongside us — validates the AI-testing category, not a competitor.
QA Wolf ~$57M raised · Series B AI + managed E2E test coverage (web + mobile) Coverage-as-a-service — their AI + QA engineers build & maintain your tests. Web-first; output is CI pass/fail, not a store-submission verdict. No compliance / security layer.
Mobileboost GPT Driver · YC · from $799/mo AI-vision mobile test authoring (natural-language steps) Closest "agentic" authoring — but runs inside XCUITest / Espresso / Appium. "Release gating" = CI pass/fail; no security, compliance, or cross-store certification.
Firebase Test Lab Google Free Robo crawler + device access Android only. No compliance. No fix prompts. No incentive to block submissions to its own store.
Aucert A release signal + fix prompt Independent · cross-store · cross-customer learning · 6-surface embed · OSS install base.
What about Cursor / Copilot / Apple / Google building this? The maker-checker logic, in detail.
08 / 10 EARLY SIGNALS

Pre-launch. Five design partners in motion. Launch August 2026.

JUNE 2026
BUILD
AUGUST 2026
LAUNCH
H2 2026
PIPELINE
BUILD
  • Working CLI: aucert validate
  • LLM cascade — Haiku → Sonnet → Opus, end-to-end
  • Rule pack: 5.1.2(i), iOS 17/18, top-20 Play flags
DESIGN PARTNERS · FIVE
  • 3 named · enterprise + mid-market
  • 2 stealth · fintech & mobile commerce
  • All five in active product feedback loops
SHIPPING — AUGUST
  • Cloud device farm — top 20 Android + iOS
  • AI behavioral testing layer
  • GitHub Action · OSS CLI · Web dashboard
Design partners · in flight
PhonePe
Enterprise · fintech
Verbal commit
Beans.ai
Beans.ai
Mid-market · logistics
In conversation
Piston
Piston Technologies
Mid-market · mobility
In conversation
Stealth
Stealth · fintech
Mid-market
Warm intro
Stealth
Stealth · commerce
Mid-market
Warm intro

The right pre-seed signal: validated pull before a dollar of GTM spend — five teams leaning in pre-launch, led by a founder relationship at PhonePe. We're raising to convert this demand, not to discover it.

09 / 10 THE ASK
$3M
18-MONTH RUNWAY · AUGUST 2026 LAUNCH

USE OF FUNDS

Product 45%
Team 30%
GTM 20%
DP 5%

QA / TESTING COMPARABLES

Tricentis
$4.5B / $425M[29]
BrowserStack
$4B / $381M[8]
Sentry
$3B / $100M[22]

Mobile testing alone is tens of billions in aggregate value. We're playing in a proven category — with an AI-native wedge, a regulated gate, and a network that compounds.

invest@aucert.ai  ·  Vivek Soneja & Rajesh Kumar

10 / 10 SUMMARY
THE PROBLEM
6.5× QA-to-dev ratio,
post-AI

Built at AI speed. Shipped at QA speed.

AI collapsed development time. Verification capacity never moved — features pile up in queue or leak to users.

3.5M+ apps rejected by Apple & Google in 2025 · 39.5% of teams above a healthy change-failure rate.
Slide 03 THE ASK
$3M
Pre-seed · 18-month runway
  • Launch August 2026
  • 5 design partners in motion
  • PhonePe verbal commit
Slide 09 THE PRODUCT
Understand, don't script

One place to govern every expectation.

Three engines, one system — Product Intelligence, a compounding Policy Library, and Validation Governance. Set an expectation once; enforced across every product.

Slide 05 THE MOAT
3 moats,
all compound

Three moats that compound.

Product Intelligence · Policy Library · Verification Cascade — each deepening with every release.

Slide 07 THE TEAM
Shipped to billions.

We've lived this problem — we owned the mobile release pipeline through every store-review cycle Aucert now automates.

Vivek Soneja · CEO
Android since Cupcake · WhatsApp, Meta, Flipkart, PhonePe
Rajesh Kumar · CTO
Payments & compliance systems · PayPal, Multiplier
WhatsAppMetaFlipkartPhonePePayPalMultiplier
Not learning the problem — we shipped it, at scale, for a decade.
Slide 02 THE INSIGHT
maker ≠ checker

Validation, not testing.

A decision, not a test tool — judged against expectations and policy, with the product depth to know the difference. Autonomous, and always re-checking as policies, threats, and releases change.

Slide 07
Open for questions — tap any tile to jump back invest@aucert.ai
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