Fibery

Give your Fibery workspace an AI voice that talks to customers

Customers ask about project status, deliverables, and timelines. Your AI agent queries Fibery entities in real time, surfaces the exact information needed, and keeps conversations moving without pulling your team away from deep work.

Chosen by 800+ global brands across industries

Work management at conversation speed

Your AI agent taps directly into Fibery's flexible databases, retrieving tasks, features, and project details the moment a customer or stakeholder asks.

Fibery

Use Cases

Project conversations, handled

See how teams using Fibery let their AI agent field questions about tasks, timelines, and deliverables while they focus on building.

Client Status Updates Without Meetings

A client messages asking about the progress on their feature build. Your AI Agent queries Fibery for all entities in their project space, filters by active status, and returns a breakdown of completed, in-progress, and upcoming tasks with estimated dates. The client gets a real-time status report. Your product team skips yet another status call.

Bug Reports That Route Themselves

An end user reports that the checkout page is broken. Your AI Agent gathers the details during the conversation, creates a Fibery entity under the Bug type with severity, reproduction steps, and the user's browser info, then assigns it to the engineering team. The bug enters your sprint board immediately. No one copies and pastes from a chat window.

Feature Requests Captured at the Source

A prospect on your website says they need bulk CSV import support before signing up. Your AI Agent creates a Feature Request entity in Fibery with the prospect's company name, the requested capability, and a priority tag. Product discovery starts with real customer demand already documented, not secondhand recollections from a sales call.

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Fibery

Fibery

FAQs

Frequently Asked Questions

How does the AI agent query tasks and features inside my Fibery workspace?

The agent uses Fibery's Commands API to query entities by type, such as Project/Task or Product/Feature. It sends a structured request specifying the fields to return and any filters like status or assignee. Results come back in real time so the agent can summarize them conversationally for the customer.

Can the agent create entities in any custom Fibery database I've built?

Yes. The agent uses Fibery's entity creation endpoint with a fully qualified type name like YourSpace/YourType. Any database you have configured in Fibery is accessible, including custom fields, relations, and rich text descriptions. Your workspace structure is fully respected.

What credentials does Tars need to connect to Fibery?

You provide your Fibery workspace subdomain and a personal API token. Generate the token from your Fibery settings under API Tokens. The token scopes determine what the agent can read or write. You can revoke access at any time from your Fibery workspace settings.

Does Tars store copies of my Fibery project data?

No. The agent queries your Fibery workspace live during each conversation. Entity details, task statuses, and file references are fetched in real time and used only to respond to the active conversation. Tars does not maintain a separate database of your workspace data.

Can the agent handle Fibery's bi-directional relations when updating entities?

Yes. When updating or creating entities, the agent passes relation fields as objects with fibery/id keys, which Fibery resolves into proper bi-directional links. If you assign a task to a user or connect a bug to a feature, both sides of the relation update correctly.

How is this different from Fibery's built-in automations?

Fibery automations trigger on internal workspace events like field changes or due dates. Tars AI Agents handle external conversations with customers and stakeholders, turning those interactions into Fibery entities or queries. They work together: the agent creates the entity, and your Fibery automation handles what happens next.

What happens if a customer asks about an entity type that doesn't exist in my workspace?

The agent handles this gracefully. If the queried type returns no results or the type name is not found, the agent lets the customer know it could not locate the information and offers to connect them with a team member or suggests alternative queries.

Can the agent run complex queries across multiple Fibery spaces at once?

Yes. The agent can execute GraphQL queries against your Fibery workspace, which supports cross-space joins and nested data retrieval. This means it can pull a feature from Product Discovery and its linked tasks from Engineering in a single request.

How to add Tools to your AI Agent

Supercharge your AI Agent with Tool Integrations

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

We’ll never let you lose sleep over privacy and security concerns

At Tars, we take privacy and security very seriously. We are compliant with GDPR, ISO, SOC 2, and HIPAA.

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