Teamcamp
Feature requests, bug reports, and project updates flow in from customer conversations. Your AI agent captures them as Teamcamp tasks with the right project, assignee, and priority, so nothing falls through the cracks. Your team works from organized tasks instead of scattered messages.
Your AI agent bridges the gap between customer conversations and Teamcamp project boards, creating tasks, checking progress, and keeping work organized in real time.
Teamcamp
See how teams use AI-powered Teamcamp integration to capture work items from conversations and keep projects moving forward.
A customer describes a rendering issue on mobile during a support chat. Your AI Agent extracts the key details, creates a high-priority task in the relevant Teamcamp project with the bug description, assigns it to the front-end team, and adds a 'bug' label. The customer gets confirmation their issue is logged. Your developers find a well-documented task waiting in their queue the next morning.
A client messages asking for a progress report on their website redesign. Your AI Agent pulls all tasks from their Teamcamp project, filters by status, and presents a breakdown: 8 tasks completed, 3 in progress, 2 not started. The client gets their update instantly. Your project manager avoids scheduling yet another status meeting.
During a sales conversation, a prospect mentions three features they would love to see. Your AI Agent creates individual Teamcamp tasks for each request in the product backlog project, tagged with 'feature-request' and the prospect's company name. Product managers review structured requests instead of digging through chat transcripts.
Teamcamp
FAQs
The agent retrieves your project list from Teamcamp and matches based on context. If a customer reports a bug on your mobile app, the agent identifies the mobile project by name. You can also configure default projects for different conversation types so routing is automatic.
Yes. The Create Task endpoint accepts assigneeIds, so the agent can assign tasks to one or multiple team members. You can set routing rules so front-end issues go to your UI developer, billing questions go to finance, and so on based on conversation context.
The agent populates the task title, description, priority level, due date, labels, assignees, and watchers. The task description includes relevant conversation context so the assignee understands the issue without needing to read the full chat transcript.
Tars requires an API key that grants access to project listing, task creation, and task retrieval. The specific permissions depend on your Teamcamp API key configuration. You do not need to share admin credentials.
Yes. The Get Task List endpoint supports filtering by status (open, in_progress, done), assignee, project ID, and date ranges. The agent applies these filters based on what is being asked to return precise, relevant task lists.
The agent checks the project list first. If no matching project is found, it informs the user and can suggest similar project names or offer to create the task in a default project. No orphan tasks are created without a valid project ID.
Yes. Teamcamp's Create Task endpoint supports a parentId parameter. The agent can create subtasks nested under an existing parent task, which is useful for breaking complex customer requests into smaller actionable items.
Manual logging requires switching between your chat tool and Teamcamp, copying details, and formatting tasks. With Tars, the agent captures everything in real time during the conversation, creating properly structured tasks with labels, assignees, and context automatically. Nothing gets lost between tools.
Don't limit your AI Agent to basic conversations. Watch how to configure and add powerful tools making your agent smarter and more functional.
Privacy & Security
At Tars, we take privacy and security very seriously. We are compliant with GDPR, ISO, SOC 2, and HIPAA.
Email - sales@hellotars.com
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