Build consistent test cases with AI prompts designed for web, mobile, and API testing — stronger prompts, stronger tests, every time.
Short, direct prompts return complete, multi-step test flows — covering positive and negative paths, consistently from one writer to the next.
Write a short prompt; get a multi-step test flow covering both positive and negative paths.
Explore the AI testing suiteStore approved prompts in a shared library, so every team produces consistent output.
See Pro featuresStronger instructions expand coverage — without rewriting the prompts you already trust.
Continuous testingPrompts target behaviours across interfaces, devices, and REST or GraphQL endpoints.
Test REST & GraphQL APIsCombine prompts with tables, Figma notes, user stories, or PRDs for richer test cases.
AI data validationGenerated tests stay green with auto-healing as the application evolves.
AI self-healingBuild, generate, review, and reuse — the full prompt workflow in one place.
GeneratorflowInstructions become step-by-step tests — with selectors, conditions, data sets, and API calls.
Prompt typeslibraryOne prompt syntax, many outputs — from boundary datasets to iOS/Android flows and recovery paths.
Prompt librarysharedStore and reuse approved prompts across web, mobile, and backend teams — consistent every run.
Reviewv1 → v2See the output, adjust the prompt, regenerate — a new, stronger version in seconds.
UI steps, selectors, conditions, and data.
Positive, negative, and boundary datasets.
Requests, assertions, and schema checks.
iOS and Android gestures and flows.
Edge cases and recovery paths.
Prompts generate tests that mirror how your product actually works.
Shared prompts keep output identical from one writer to the next.
Built-in guidance steers everyone toward strong prompting patterns.
Prompt engineering works across the whole ContextQA platform.
It's the process of writing clear inputs for an AI system so it produces accurate, complete outputs. In ContextQA, that means using prompts to generate test cases, scenarios, and flows based on your product requirements.
A prompt engineer writes the instructions the AI uses to build test cases. The system handles generation, while the engineer reviews and adjusts prompts when needed.
The system reads the prompt, identifies flows, data, and behaviours, and produces a full set of test steps including selectors, conditions, data sets, and API calls.
Short prompts with clear actions, user roles, data values, and expected outcomes produce the most accurate tests.
Yes. You can store, edit, and reuse prompts across teams so outputs stay consistent.
The platform removes the need for specialist roles by guiding teams toward strong, reusable prompting patterns.
See ContextQA turn plain-English prompts into accurate, repeatable tests — live, on your app.
Book a DemoWhat you test
Catch hallucinations and drift before users do
SAP, Oracle, Workday & custom ERP
Browser automation across every engine
Native iOS and Android coverage
REST and GraphQL validation
CRM workflow automation
Enterprise application coverage
See what a code change breaks before merge
How you test
Plan, track, and manage every test
Tests repair themselves as code shifts
Pinpoint why a test broke, instantly
Catch unintended UI change
Load and stress at scale
Always-on across every release
Platform & AI
Parallel cloud grid, every browser and device
One prompt drives 50 testing tools
Test assets and code export
Real user intelligence and analytics
Connect Jenkins, Jira, CI/CD
IBM, Coforge, Red Hat
Analyze End-To-End Tests
Platform & AI
Not three tools.
