MacPaw Launched AI Platform to Automate IT Support
The new Leebry platform uses internal data to resolve level 1 support tickets and automate team access provisioning.
Updated on Oct. 3, 2026 in Remote Work
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MacPaw has officially launched Leebry, an AI platform designed to automate level 1 IT support and user access provisioning. The software surfaces answers from internal documentation and threads to reduce repetitive internal help desk queries.
Why it matters
The platform was developed to address inefficiency in corporate knowledge management, where teams struggle with repeated questions already documented. It provides a mechanism for companies to bridge the gap between executive AI expectations and actual team capabilities.
During testing, the platform resolved 30% of level 1 IT tickets. Industry surveys indicate 90% of companies deploy AI without auditing internal knowledge bases, while 6 in 10 IT leaders report a disconnect between leadership expectations and team capabilities.
The players
MacPaw
A software development company that specializes in utility applications and creates tools for IT and workspace management.
The details
Leebry functions as a Slack bot that extracts and surfaces information from a company's internal documentation, intranets, and communication threads. To ensure accuracy, the platform includes an MCP server with administrator-set guardrails and links every AI-generated response back to its original source. It also handles user authentication to ensure agents only access data permitted by their specific user role.
Timeline
2025: Leebry began as an internal hackathon project.
2026: MacPaw released its AI at Work report.
October 3, 2026: MacPaw launched the Leebry platform.
Market Landscape
The launch of Leebry follows findings in the 2026 AI at Work report, which highlighted significant failures in how companies manage their internal data before deploying AI agents. It marks a shift toward operationalizing AI tools that prioritize source verification over broad generative capabilities.
IT managers should evaluate their current level 1 ticket volume to determine if internal knowledge base automation could yield similar efficiency gains. Before deploying similar agents, verify that your internal documentation is indexed and that your AI implementation includes source-linking features to maintain data accuracy.
The takeaway
The primary insight is that automating routine IT support requires a foundation of clean, searchable internal documentation. Operators should prioritize auditing their existing knowledge bases before investing in AI tools that aim to automate agent-facing responses.
Further reading
Learn more about the evolving operational strategies for Remote Work.
Source note: This article includes information reported by 9to5Mac.
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