Shipwithout fear.
Viziera test-drives your app like a real user — automated QA on every commit, AI-led beta testing between releases.
Scripted QA whenyou know what to test.AI explorationfor everything else.
Two testing surfaces, one desktop app. Block bad merges with deterministic scenarios; surface the bugs you didn't script with an autonomous AI tester.
App Testing
Author scenarios in plain language. Viziera runs them on every PR with self-healing selectors, multi-viewport coverage, and video evidence — and posts results back to your repo.
Beta Testing
An autonomous AI user logs into your product, crawls through every reachable flow, and files reproducible findings with screenshots, repro scripts, and severity rankings.
A testing stackthat sees whatyour users see —and does whatthey would do.
Viziera runs on your machine, drives your product through real OS-level input, and stores findings in a local database. No flaky cloud runners. No selectors that break on every refactor. Just the same actions a user would take, every time you ship.
Desktop Driver
Real mouse, keyboard, and screen — not a headless browser
AI Beta Tester
Autonomous exploration that files reproducible findings
Workflow Engine
Branching, parallel steps, and approval gates around runs
Findings Database
Local SQLite + artifacts — your test data stays on your machine
CI + Integrations
Webhooks, status checks, Slack, Linear, Jira, GitHub
Viziera Stack
Local-first · cross-platform
Built for teamsthat hate flake.
Every Viziera primitive was built because a previous QA tool failed us on it — flake, brittle selectors, missed regressions, blind spots in CI.
Self-healing scenarios
When a selector breaks, Viziera falls back to text, aria, and semantic matches — so your suite survives refactors instead of going red.
Autonomous bug discovery
An AI tester explores your product like a real user — finding dead-ends, visual bugs, and broken flows you never wrote a scenario for.
Visual regression
Pixel-perfect diffs against approved baselines, with masking and viewport awareness.
analysis + recommendation
Multi-step chain
4 sources, 12 docs
Pricing elasticity
Waiting
Local-first by default
Test data and screenshots live in local SQLite + your filesystem. Webhook secrets and GitHub tokens go to the OS keychain via keytar. No cloud lock-in.
of actions audited
Ships with your PR
Token-authed webhooks, GitHub PR comments with screenshots, and Slack / Linear / Jira routing.
Five test surfaces.One desktop app.
Deterministic scenariosthat block bad merges
Author scenarios in plain language. Viziera drives the browser, retries flaky steps, and posts pass/fail back to your PR with screenshots and video. Self-healing selectors mean fewer 3am false alarms.
An AI user that findsthe bugs you missed
Logs into your product, crawls the reachable surface, and reports findings ranked by severity. Visual bugs, dead-end flows, broken forms, accessibility violations — each one with a repro script.
Pixel-diff every screenyou ship
Approve a baseline once. Viziera screenshots every meaningful state on every run, masks the parts that legitimately change, and surfaces only the pixels that shouldn't have moved.
WCAG evidence onevery release
Injects axe-core on every page, ranks violations by impact, and produces the per-page compliance report your procurement team keeps asking for.
Production-scale runsfrom your CI
Drive 150K-scale pytest suites with streaming progress, error-trend grouping, and SLA thresholds. Same workflow engine, same reports — just bigger numbers.
0%
Pass rate in pilots
0
Bugs found week one
0+
Steps per scenario
0K
Load test scale
Test like a user.Ship like a pro.
Early access is rolling out in small batches. Tell us about your stack and we'll get you a build.