Confluence

WikiFix is a Confluence app for administrators and knowledge leads that scans selected spaces for outdated, contradictory, duplicate, and ownerless pages. It reads page content to detect conflicting claims, presents the relevant passages side by side, and lets a reviewer choose the claim to keep before applying the change. WikiFix writes nothing without approval; content fixes can be reverted in one click, while reassigning an abandoned page owner is identified as a non-reversible action. It runs inside an existing Confluence installation, can notify page owners through inline comments, and scans new or changed pages using credits billed through the Atlassian Marketplace.

WikiFix is an AI-powered Confluence app that monitors selected spaces for outdated, contradictory, duplicate, or ownerless pages. It reads page content rather than filtering only by dates, compares conflicting claims side by side, and presents findings for review. An administrator chooses the authoritative claim; WikiFix then proposes the edits, requires approval before writing, and allows content changes to be reverted in one click. It can also reassign abandoned pages or post an inline comment mentioning the page owner and space administrators. WikiFix runs inside an existing Confluence installation and is billed through the Atlassian Marketplace, with payments converted into scan credits for new or changed pages.

Confluent is an event-streaming platform used in the described system to carry live event messages from a win-probability system to downstream processing. That processing determines whether an event is a key moment and generates explanatory text.

Merge is a connective infrastructure platform and universal context engine for AI agents, developed for companies building internal and customer-facing AI products. It connects agents to company data, tools, and models, with capabilities for authenticated tool access, LLM routing, customer-data synchronization, workforce access control, shared skills, and security auditing. Its context-layer approach combines synchronized copies of large datasets with live API lookups. A router selects between cached or live context, a summarizer derives higher-level context, and company skills and memory encode organizational definitions and procedures. The system also tracks data provenance, including where context came from and when it may become invalid.

A remote Model Context Protocol (MCP) server from Atlassian that lets MCP-compatible AI clients retrieve and work with live Jira and Confluence content. It applies the user's existing Atlassian permissions, allowing permission-aware access without maintaining a separately embedded retrieval-augmented generation data pipeline.