95% of enterprise AI pilots fail to deliver measurable ROI (MIT, 2025 State of AI in Business Report). But the teams getting real results, with lower ticket volume, higher deflection, and agents that actually hold up in production, aren't running better models. They built a better knowledge layer.

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In this session, Brainfish CEO Daniel Kimber breaks down how three organizations made AI support work. What they changed, what they kept from their existing Zendesk, Slack, and Microsoft Teams stack, and why they landed in the 5% that delivered measurable ROI.

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WHAT WE'LL COVER:

• Cybersecurity SaaS · 5,000 monthly tickets, an audience that catches wrong answers instantly. Kept Zendesk and Slack. Added Brainfish as the knowledge layer inside both. Result: 80% of inbound chats automated, 50% headcount growth avoided, 2 to 3 second response times.

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• Legal tech · 4 products, 200+ pricing and plan combinations, one generalist help center talking to every customer the same way. How they restructured 12 segmented knowledge bases and routed email replies through Zendesk. Result: 74% ticket reduction, +37-point NPS lift, 98% answer accuracy.

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• US city government · 600 staff, paper SOPs, multilingual workforce. How they used video-to-SOP to convert procedures in three native languages (English, Spanish, Haitian Creole) and deployed AI chat inside Microsoft Teams for 300+ staff.

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• The MCP era · How Claude, Cursor, and VS Code Copilot can now search, draft, audit, and update your knowledge layer. Live walkthrough of the Brainfish MCP.

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WHO THIS SESSION IS FOR: Heads of Support. CX leaders. Anyone who said yes to the AI investment and now has to make it work. If your Zendesk or Intercom AI agent is live and underperforming, if your help center articles go stale faster than your team can update them, or if you're trying to decide what to build before you deploy more AI tooling, this session is where to start.