From user story to raised defect — without writing the test
Connect RobotActions to Jira, Azure DevOps or TestRail. The AI agent reads your stories and acceptance criteria, generates test scenarios, runs them on real Android, iOS and browser sessions, and raises defects directly back into your ALM. Use our in-house AI with prepaid credits, or bring your own — Anthropic, OpenAI, Google, OpenRouter or xAI.
Seven capabilities. One end-to-end QA workflow.
Each one works standalone. Together they cover the full path from a ticket in your backlog to a defect raised against a verified failure on a real device.
Jira, Azure DevOps and TestRail integration
One section stores your auth tokens for Jira, Azure DevOps and TestRail. The agent uses them to read stories, acceptance criteria, and to raise defects back into the same ALM.
Reads stories and acceptance criteria
The agent pulls the full user story and its ACs as first-class context — so every test scenario it generates is grounded in what 'done' actually means for that ticket.
Test scenario generation
Point the agent at a story and it generates the test scenarios — happy path, edge cases, negative paths — derived from the acceptance criteria.
Execution on real devices and browsers
Every generated scenario runs on real Android, iOS and browser sessions in the RobotActions device cloud. No emulators, no simulators.
Raises defects automatically
Any failure becomes a defect raised directly into Jira, Azure DevOps or TestRail — with logs, screenshots and the failing scenario attached. No manual triage step.
Test data and env URL vault
Store test data, environment URLs and any other QA-task secrets in a vault the agent can pull from at run time. No copy-pasting between systems, no plaintext credentials.
Bring your own AI — or use ours
Use the in-house AI with prepaid credits, or plug in your own model provider — Anthropic, OpenAI, Google, OpenRouter or xAI. You pick the model and pay for it directly; we run the QA workflow on top.
How a story becomes a raised defect
One continuous workflow. The agent stays in the same context from the original ticket to the defect raised against a verified failure.
- Step 01
Connect your ALM
Store your Jira, Azure DevOps or TestRail auth token once. The agent reuses it for every run.
- Step 02
Read story + ACs
Agent pulls the user story and its acceptance criteria as the grounding context for every scenario it generates.
- Step 03
Generate test scenarios
Test scenarios — happy path, edge cases, negative paths — generated from the ACs.
- Step 04
Execute on real devices
Every scenario runs on real Android, iOS and browser sessions, using test data and env URLs pulled from the vault.
- Step 05
Raise defects in your ALM
Failures become defects in Jira, Azure DevOps or TestRail — with logs, screenshots and the failing scenario attached.
- Step 06
Your AI, your control
Pick the AI model that runs the workflow: in-house (prepaid credits) or bring your own provider. Same workflow, your choice of brain.
Plugs into the ALM your team already uses
One connection per ALM. The agent reads stories and raises defects across your existing surface.
Stop writing the same test twice
Let the agent read the story, generate the scenarios, run them on real devices and raise defects. Your team reviews and ships.