How to Build an AI Agent for Confluence and Notion

The workflow problem

Companies outgrow their documentation platforms. A startup that began on Confluence when the founding team came from an enterprise background may find that new hires prefer Notion’s flexibility, or an acquisition may bring two teams with incompatible knowledge stacks. The result is the same: critical information split across two systems, with no one sure where the canonical version lives.

Manual migration is brutal. Confluence organizes content in spaces, pages, and child-page hierarchies with inline macros, Jira links, and page-level permissions. Notion uses databases, nested pages, blocks, and relation properties. Simply exporting Confluence to HTML and importing into Notion produces flat, broken documents. Someone has to manually rebuild the hierarchy, relink cross-references, reattach files, and verify that nothing was lost. For a mature Confluence instance with hundreds of spaces, this is a multi-month project that nobody volunteers for.

Even after migration, many teams keep Confluence running for legacy content or because some departments refuse to switch. Now you have two search silos. Engineers search Notion; the legal team searches Confluence; nobody finds what they need on the first try.

Why an AI agent, not just automation

A simple export-and-import script cannot handle the semantic translation between two fundamentally different document models. Confluence macros like {status}, {jira}, or {expand} have no direct Notion equivalents. A rules-based script either drops them silently or produces garbled markup.

An AI agent reads each Confluence page, understands its intent, and makes intelligent decisions about how to represent that content in Notion. A status macro becomes a Notion status property on a database entry. A Jira link becomes a bookmarked URL with context about the ticket. An expand block becomes a toggle heading. The agent preserves meaning, not just markup.

For cross-platform search, the agent does more than keyword matching. When a user asks “What’s our data retention policy?”, the agent understands that the answer might live in a Confluence space called “Legal Compliance” or a Notion database called “Policy Register.” It searches both, ranks results by relevance and recency, and returns a unified answer with links to the source document in the correct platform.

How it works with ACP

The Agentic Control Plane provides OAuth-secured connectors for both Confluence (via Atlassian OAuth 2.0) and Notion (via Notion’s integration token or OAuth). Once connected, the agent has access to specific tool actions.

Confluence tools available: Read spaces and pages, search content with CQL (Confluence Query Language), list page attachments, read page properties and labels, and retrieve page hierarchy trees. The agent cannot modify Confluence content unless explicitly granted write scopes.

Notion tools available: Create and update pages, create and modify databases, add blocks (text, headings, toggles, callouts, bookmarks, files), set page properties, search across the workspace, and manage relations between database entries.

The agent uses these tools in a structured migration workflow. It first reads the Confluence space tree to understand the hierarchy. Then it creates a matching Notion structure, translating spaces into top-level pages or databases depending on the content type. For each Confluence page, it reads the content, identifies macros and special elements, and creates the corresponding Notion blocks.

Here is a realistic example of the agent handling a cross-platform search after migration:

User: Find everything we have about the SOC 2 audit preparation process.

Agent: I searched both platforms. Here is what I found:

• Confluence (Legal space): “SOC 2 Audit Checklist 2025” – last updated Jan 15, 2026. Contains the formal checklist with 47 controls. [Link to Confluence page]
• Notion (Security DB): “SOC 2 Prep Tracker” – actively maintained, 32 of 47 controls marked complete. [Link to Notion database]
• Notion (Engineering wiki): “Infrastructure Controls for SOC 2” – technical implementation details for controls CC6.1 through CC6.8. [Link to Notion page]

The Confluence checklist appears to be the original source document, while the Notion tracker is the active working copy. Would you like me to check if the Notion tracker is in sync with the latest Confluence checklist?

This kind of intelligent cross-referencing is only possible because the agent understands the content semantics, not just file names.

Governance and security

Knowledge migration is one of the highest-risk operations you can perform, because documentation often contains sensitive material: security policies, employee data, financial figures, and customer information. ACP enforces strict boundaries at every step.

Confluence OAuth scopes: The agent requests read:confluence-content.all and read:confluence-space.summary for migration and search. Write access to Confluence is not requested unless you explicitly configure bidirectional sync. The agent cannot delete Confluence pages under any scope configuration.

Notion OAuth scopes: The agent requests access to insert content and search the workspace. Notion’s integration model allows you to share specific pages or databases with the integration, so the agent only sees what you explicitly grant. Sensitive HR or finance databases can remain invisible to the agent entirely.

Data residency: ACP does not store document content at rest. Content is read from Confluence, transformed in-memory, and written to Notion in the same operation. The agent retains no copies of your documentation.

Audit trail: Every page read, every page created, every search query is logged with the authenticated user identity, timestamp, tool used, and action taken. If a page is migrated incorrectly, you can trace exactly what the agent read and wrote. Compliance teams can export these logs for audit evidence.

Permission boundaries: The agent inherits the permissions of the authenticated user. If your Confluence account cannot access a restricted space, neither can the agent. This prevents accidental exposure of sensitive content during migration.

Example use cases

• Full space migration: A 200-page Confluence engineering wiki is migrated to Notion as a structured database with properties for owner, status, and last review date. The agent preserves the page hierarchy and converts Jira links to bookmarks with ticket summaries.

• Incremental sync: Teams that cannot fully switch maintain both platforms. The agent watches for new Confluence pages in specified spaces and creates corresponding Notion entries, keeping both systems current without manual copy-paste.

• Unified search portal: Customer success managers ask natural-language questions and receive answers sourced from both platforms. The agent cites the specific page and indicates which platform it came from, reducing time-to-answer from minutes to seconds.

• Content audit: Before migration, the agent scans all Confluence spaces and produces a Notion dashboard showing page counts, last-modified dates, orphaned pages with no links, and spaces with no recent activity. This helps teams decide what to migrate and what to archive.

• Macro translation report: The agent identifies every Confluence macro in use across the instance and generates a mapping table showing how each one will be represented in Notion, flagging any that require manual review.

Getting started

Building a Confluence-to-Notion agent takes just a few steps:

1. Sign up at cloud.agenticcontrolplane.com and create your first workspace.
2. Connect your tools by linking your Atlassian account (for Confluence access) and your Notion workspace through the Data Sources page. ACP handles OAuth so you never share passwords.
3. Describe your agent in plain English: “Migrate the Engineering space from Confluence to a Notion database, preserving page hierarchy and converting macros to native Notion blocks.” The agent will plan the migration and ask for confirmation before writing anything.