HeyAI
Project Intelligence
Frequently asked questions
Learn what HeyAI does, how teams get started, how the product is used day to day, and how it works with Azure DevOps, Jira, private Azure deployments, and MCP.
Product basics
HeyAI reviews backlog items with project context so teams can make better requirement, testing, and release-readiness decisions.
Users get source-backed requirement gaps, clarifying questions, test scenario drafts, RBT recommendations, and release confidence signals. The practical value is less manual review, fewer late requirement surprises, and testing decisions that are easier to explain.
HeyAI is for product owners, QA leads, delivery managers, engineering leads, and teams that manage delivery in Azure DevOps or Jira.
No. Ask HeyAI is one capability, but the product is focused on project intelligence: backlog readiness, test coverage, RBT recommendations, project Q&A, and reviewable delivery evidence.
No. HeyAI drafts recommendations and evidence for human review. Teams decide what to accept, edit, reject, or route back into their delivery workflow.
Getting started
The fastest path is to connect one Azure DevOps or Jira project and review a small set of real backlog items.
Using HeyAI
Open the HeyAI app, choose Azure DevOps or Jira, initialize or select a project, then analyze a work item or issue. HeyAI reviews the item and returns gaps, questions, tests, and RBT guidance.
Ask HeyAI answers project questions using the initialized project context, such as requirement details, risk areas, testing coverage, release readiness, and linked delivery evidence.
Yes. HeyAI drafts practical test scenarios across happy path, negative, edge-case, integration, regression, and data coverage. Teams can edit or reject the output before using it.
RBT means risk-based testing. HeyAI recommends whether a backlog item should be manual, automated, hybrid, skipped, investigated, or blocked, with rationale and confidence.
For Azure DevOps, HeyAI can post approved gap questions back through the extension flow. Jira support is focused on hosted app analysis and project context today; write-back behavior should be reviewed with the HeyAI team for your setup.
Integrations and deployment
Yes. HeyAI supports Azure DevOps and Jira as delivery systems, with dedicated pages and setup flows for each.
HeyAI can use backlog items, acceptance criteria, comments, requirements, docs, decision records, test evidence, incident context, and other connected project information depending on the setup.
Yes. Private Azure deployment is available for teams that need project data, vectors, logs, connector credentials, and AI keys to stay in the customer's Azure subscription.
HeyAI MCP lets MCP-capable agent clients such as GitHub Copilot access authenticated HeyAI project intelligence, scoped to the signed-in user's allowed projects.
HeyAI is designed to show uncertainty instead of inventing confidence. When project context is weak, it should surface what is missing and recommend the next clarification step.
Ready to see it with your own workflow?
Choose the page that matches where your team manages backlog items today.