Local-first · Works offline · Production-ready

Test automation
that actually learns

QA Brain explores real applications, captures element fingerprints and navigation flows, then generates Playwright tests from accumulated knowledge. Every run makes the system smarter.

99%
Selector Confidence
<20ms
Error→Test
5,800+
Tests Passing
170K
Lines of Code

Four phases. Zero hallucination.

Unlike tools that generate selectors from thin air, QA Brain first learns from the real application — then generates from knowledge.

01

Explore

Autonomous browser exploration discovers forms, interactive elements, and page structure. No LLM needed.

02

Learn

Element fingerprints captured across 7 dimensions — tag, ARIA role, label, text, nearby context, parent, type.

03

Generate

Deterministic codegen produces Playwright tests from learned patterns. Same input, same output. No variance.

04

Self-Heal

When selectors break, fingerprint matching finds the element's new location. Three-tier fallback: exact → fuzzy → LLM.

Each cycle feeds the next. Selectors reach 99% confidence through repeated validation.
qa-brain explore
$ qa-brain explore https://app.example.com/login --generate Phase 1: Discovery Analyzing page structure... ✓ Found 1 form, 3 interactive elements, 2 links Phase 2: Goal-Oriented Exploration [1/1] Log in using discovered credentials ✓ 4 actions completed Phase 3: Test Generation ✓ Saved: tests/exploration/login_test.spec.ts Memory Updated: Selectors learned: 3 | Transitions: /login → /dashboard (0.99 conf) Fingerprints stored: 3 | Confidence: 100% high

13 provisional patents filed

Covering the core mechanisms of learning-based test generation, self-healing, and progressive intelligence.

#1
Closed-Loop Autonomous Test Intelligence System
63/940,252
#2
Multi-Source Governance and Remediation for AI-Generated Tests
63/872,024
#3
Progressive Test Intelligence Using Local Memory
63/859,841
#4
Bayesian Confidence Scoring for Learned Selectors
63/929,028
#5
Automated Test Generation from Error Analysis
63/858,068
#6
Reconstructing User Action Sequences from Error Reports
63/860,827
#7
Origin-Aware Test Quality Assessment
63/860,778
#8
Objective-Initiated Exhaustive Exploration
63/860,053
#9
Automated Test Decomposition with Confidence-Based Selection
63/860,688
#10
Multi-Source Pattern Learning for Test Automation
63/865,472
#11
Human Edit Tracking and Feedback-Informed Generation System with Cross-Source Conflict Detection
63/984,395
#12
Automatic Test Generation from Ticket Systems
63/865,468
#13
Multi-Dimensional Element Fingerprinting for Autonomous Test Selector Repair
63/984,402
Provisional patents expire August 2026. Strategic discussions welcome before conversion deadline.

Built for enterprise from day one

Local-first, schema-driven, no vendor lock-in. Runs air-gapped on your infrastructure.

Local-First

All AI processing runs on local LLMs via Ollama. No data leaves your network. Cloud providers are optional fallbacks, never defaults.

Ollama · SQLite · Playwright

Schema-Driven

Every LLM output follows Pydantic schemas. Deterministic code generation means same input produces same test. No hallucination in output.

Pydantic · TypeScript · JSON

CLI-First

44 commands across 10 categories. Every feature is scriptable, inspectable, and CI-ready. No dashboard required.

Click · Rich · CI/CD native

Bayesian Memory

Selector confidence scores updated via Bayesian inference. Source-weighted priors. Domain-scoped to prevent cross-site contamination.

Patent #3 · Patent #4

Self-Healing

Three-tier selector repair: fingerprint matching (7 dimensions), fuzzy attribute matching, LLM-assisted fallback. Automatic, transparent.

Patent #13 · 3-tier fallback

Modular Agents

Explorer, Generator, Planner, Healer, Governance — each agent is independent and swappable. No monolithic chains.

10 agents · 5 brain regions

20 years solving this problem

Neil Duggan
Founder & Architect — QA Brain

Two decades of QA engineering and automation leadership across the world's most demanding teams. Built and led testing infrastructure for products used by billions of people. QA Brain was created from direct experience with the limitations of every existing test automation approach — the fragility, the maintenance burden, the complete absence of learning between test runs.

Apple Google Nike WWE NFL Olympics FIFA World Cup 20+ years QA

See it in action

5-minute live demo on any website. No slides, no setup, just the real system.

neil@qa-brain.com →

Or connect on LinkedIn