Capabilities

Talonic includes an embedded AI agent accessible from every page via Cmd+I (Ctrl+I on Windows). The agent understands your workspace context and can inspect schemas, search documents, analyze extraction quality, explore cases, and build schemas — all through natural language. It serves as a conversational interface to your entire workspace, eliminating the need to navigate through multiple pages to find information or perform common operations.

The agent is context-aware, meaning it automatically knows which page you are on and what data is visible. If you open the agent from a document detail page, it already has that document in scope and can answer questions about its extracted fields, processing status, or classification without you needing to specify which document you mean.

The agent classifies every user message as either a question (answered with information) or a command (triggers an action). Questions are handled instantly with read-only access, while commands go through the impact-level system to ensure safety. The agent streams its responses in real time, so you can see reasoning unfold as it queries your workspace data.

There are important limitations to be aware of. The agent cannot access external systems or the internet — it only works with data already in your Talonic workspace. It cannot bypass permission boundaries, so team members with read-only (Viewer) access cannot use the agent to make changes. Long-running operations like full batch extractions cannot be triggered through the agent; those must be initiated from the relevant UI page. The agent also cannot modify field registry entries directly — those changes flow through the resolution pipeline.

The agent is particularly effective for onboarding new team members. Instead of reading documentation about each platform feature, new users can ask the agent questions like "How many document types do we have?", "What schemas are available?", or "Show me our most common fields." The agent provides instant, contextual answers that help users build a mental model of their workspace. This reduces time-to-productivity for new team members from days to hours.

What the Agent Can Do

The agent has deep access to your workspace and can help with:

Example Agent Interactions

The agent excels at cross-cutting queries that would otherwise require navigating multiple pages. For example, you can ask it to summarize extraction quality across your latest job runs, identify which document types have the lowest confidence scores, or compare field coverage between two schemas. The agent queries the underlying data in real time and streams results, so complex analyses that would take several minutes of manual navigation are answered in seconds.

Schema creation through the agent is particularly powerful. Describe the fields you need in plain language — for example, "Create a schema for purchase orders with vendor name, PO number, line items, unit price, and total amount" — and the agent maps each field to the registry, identifies the best match for each, and creates a draft schema ready for your review. This is faster than manually searching the registry and adding fields one by one through the schema editor.

Behind the scenes, the agent uses the same internal APIs as the web interface. When you ask "Show me all invoices processed this week", the agent queries the documents endpoint with date filters and the Invoice document type. When you ask "What is my capture rate?", it reads the telemetry data from the dashboard service. This means the agent always shows the same data you would see in the UI — there is no separate data layer or cache that could show stale results.

curl "https://api.talonic.com/v1/documents?type=Invoice&created_after=2026-05-01" \
  -H "Authorization: Bearer $TALONIC_API_KEY"

{
  "data": [
    {
      "id": "doc_7f3a1b2c",
      "filename": "invoice_2026_0472.pdf",
      "document_type": "Invoice",
      "status": "completed",
      "fields_extracted": 24
    }
  ],
  "meta": { "total": 156, "cursor": "eyJpZCI6MTU2fQ" }
}