Your team ships faster than QA can follow
AI coding accelerates delivery, but every new release adds more paths that can break.
Powered by AI and visible in one shared platform. Your dedicated engineer learns the product, owns testing from planning to release proof, and keeps every result transparent in QAFactory.ai.
AI coding accelerates delivery, but every new release adds more paths that can break.
Selectors change, data expires, and suites become noisy until engineers stop trusting them.
Recruiting, tooling, and onboarding delay meaningful coverage while production risk keeps growing.
AI accelerates scenario design, execution, and analysis. Your Forward Deployed QA Engineer owns judgment, maintenance, and the release decision.
We map the journeys that protect revenue, trust, and retention — then turn them into a living coverage plan.
AI accelerates scenarios, data, and assertions. A QA lead reviews every case before it becomes part of your suite.
Playwright and Cypress checks follow user intent, with proactive maintenance when your interface changes.
Duplicate symptoms are grouped, noisy failures are investigated, and only useful signals reach your engineers.
Critical checks run on pull requests, deploys, and schedules, with results delivered in the tools your team uses.
A dedicated QA engineer validates failures, records evidence, and gives every release a clear go/no-go recommendation.
Signup, billing, permissions, and the workflows your customers depend on.
A QA engineer separates real defects from flaky automation before your team is interrupted.
Severity, exact steps, environment, screenshots, video, logs, and a clear expected result.
Tests and test data evolve as your product changes, without becoming another engineering burden.
One click from a failed check to the replay, artifacts, and QA verdict your team needs.
Your first week focuses on the flows that can block revenue or customer trust. Each cycle expands the regression suite while keeping existing coverage healthy.
The difference is accountable ownership: someone maps risk, maintains coverage, investigates failures, and communicates the release decision.
Your QA Engineer explores staging, maps the first critical journeys, and makes ownership visible in QAFactory.ai.
Prioritized issues, reproduction steps, screenshots, and video appear in your shared platform workspace.
Manual cases and stable regression paths connect to your release cadence with execution visible to the team.
Your engineer expands coverage, investigates failures, and publishes evidence and release readiness in QAFactory.ai.
Your Forward Deployed QA Engineer and the QAFactory.ai platform work together from product discovery to release proof. There are no separate test-management fees and no disconnected dashboard your engineers have to babysit.
Design my QA plan →✓Critical user-flow map
✓Manual exploratory testing
✓Functional and regression coverage
✓Playwright or Cypress automation
✓Cross-browser and responsive checks
✓API and integration validation
✓Video, screenshots, logs, and repro steps
✓Release risk and go/no-go summary
✓Direct Slack or Teams collaboration
✓Jira, Linear, or GitHub issue filing
✓Test maintenance as the product changes
✓Weekly coverage and defect reporting
QAFactory brings test planning, execution, evidence, automation, defects, integrations, and reporting into one shared command center.

QAFactory converts approved acceptance criteria into positive and negative test cases, assigns priority, preserves traceability, and prepares every step for manual or automated execution.

Your dedicated Forward Deployed QA Engineer learns your product, users, risks, and release process. From test management and coverage ownership to execution, defect evidence, and final release proof, everything lives in the QAFactory.ai platform—with no additional platform cost during your managed QA engagement.
Manual cases, automation runs, defects, video, logs, and release status stay connected.
Bring Jira, Linear, GitHub, GitLab, Slack, Teams, CI/CD, Playwright, Cypress, and API workflows together.
Accelerate coverage ideas, failure grouping, gap detection, run summaries, and stakeholder reporting.
The platform is included at no additional software fee within your agreed managed QA plan and scope.
Offer teams, business units, or clients a QA workspace with your organization’s brand and operating model.
Give engineering, product, leadership, and client stakeholders the quality view appropriate to them.
Included with managed QA plans · White-label options for internal use
Explore the platform →Start small, prove value, and expand without a long-term contract.
A fast, evidence-rich assessment before a launch, investor demo, or major release.
A dedicated Forward Deployed QA Engineer plus the QAFactory.ai platform at no additional software cost.
Broader environments, devices, products, or embedded QA capacity for growing teams.
Month-to-month managed plans. Scope and pricing are confirmed before work begins.
They work inside your release process: learning the product, mapping risk, running tests, maintaining automation, investigating failures, and communicating actionable findings to engineering.
The QA practice of DigitX LLC — shipped and tested across SaaS, mobile, AI, payments, and API-heavy products.
From $2,499/month. Month-to-month. First results in one week.