From requirement to release evidence — five integrated layers replace the fragmented testing toolchain.
The copilot at the core: generates test cases from requirements, proposes step mappings with cited evidence, triages failures with probable root cause, and continuously optimizes coverage. Every suggestion is evidence-backed and waits for human approval — AI never approves its own work, and every decision is audited.
Quality embedded across the lifecycle — one guided Design → Map → Automate → Run workflow, an ISTQB-style Requirements Traceability Matrix, release planning with environment scope, entry/exit criteria with CAB sign-off, and audit-grade evidence from the first user story to the go-live decision.
Grid-based parallel web execution with self-healing locators, environment-aware test data injection, and step-level evidence capture on every run. API test execution ships in the same grid — request, assertions, and masked evidence in the standard report. Mobile app scanning and device farm connectivity built in; on-device execution on the roadmap.
From engineer to executive: pass/fail trends, automation coverage, risk indices, and a Release Advisor whose confidence score is computed from live pass, coverage, defect, and gate data — never a model guess. "Can we ship?" gets an evidence-backed answer, not an opinion.
Native connectors for Jira and Azure DevOps, CI/CD pipeline triggers, Slack and Teams notifications, signed webhooks, a governed REST API, device farms, and enterprise identity (SSO/SCIM). Quality gates travel with your delivery process, not beside it.
Every test travels the same four-stage journey, and every screen speaks the same language — the table, the drawer, the filters, and the audit trail all show the same stage. No mixed vocabularies, no guessing what to do next.
AI turns requirements into traced, reviewable test cases anchored to acceptance criteria.
Steps bind to your application model — evidence-backed AI proposals, human-approved; exact matches bind by policy.
Executable artifacts are generated, reviewed, and approved — hybrid manual steps stay honestly labeled.
Evidence-backed grid runs roll up into release plans and the go/no-go decision.
The three disciplines that decide whether enterprise testing scales — managed inside the platform, not in spreadsheets beside it.
Every release declares which environments it covers, every environment declares whether it is ready, and every run is scoped to where it actually ran.
Environment-aware test data with record-level bindings, masking, and full lineage — from data set to the evidence attached to every test result.
Plan the release, gate it with criteria, execute highest-risk first, and make the ship decision on live evidence.
See the platform on your applications, your data, and your release process.
TestAccel