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thinQit|Teammates

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INSIDE YOUR WORKFLOW

No new tools. No new rituals.

Teammates pick up tickets, open PRs, and report progress in the systems your team already runs.

JiraAzure DevOpsGitHubPlaywright

AI teammates FAQ

How thinQit AI teammates execute real work

Answers about roles, context and oversight in the teammate model.

What is an AI teammate in thinQit?

An AI teammate is a role-specific operator configured for a recurring business workflow. Instead of only answering prompts, a teammate receives context, works through assigned tasks and reports an outcome inside the workspace.

What kind of work can AI teammates handle?

Teammates cover specialist areas such as building, quality review, security, content and SEO. Each role has its own workflow and tools, while shared workspace context keeps related work aligned across the team.

How do people stay in control of teammate work?

Teams define the task, context and approval expectations for each workflow. Drafts, evidence and status updates make the work reviewable, so publishing or production changes can follow the level of oversight the organisation requires.

Explore related thinQit pages

See the build workspace See shared context Read teammate guides