Harmony
AI agents that resolve IT/HR tickets inside Slack and Teams
284 followers
AI agents that resolve IT/HR tickets inside Slack and Teams
284 followers
Harmony is an AI-native ITSM platform for IT teams. Instead of bolting a chatbot onto a ticketing tool, we built the helpdesk around AI agents: employees ask in Slack or Teams, and 100+ production-ready agents handle password resets, app access, onboarding, device issues and more end to end, escalating to a human only when needed. Ticketing, asset inventory, SaaS management and workflows live in one workspace, so agents have context to act. Teams hit 60%+ auto-resolution in days.
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Build your Framer site from Claude, Codex or CursorYour AI agent builds it. You review before it goes live.
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Harmony dev here, so pinch of salt. Everyone asks about the agents, but most of the hard part was identity. The person asking in Slack has to be provably the same human as the Okta user, the Jamf device owner and the HiBob record, and their name is spelled three different ways across those. Get that right and the agent part almost falls out. Get it wrong and you've built something that confidently resets the wrong person's password.
The hardest part of building internal tools isn't the model, it’s getting reliable context out of your corporate tools. If your HR suite, MDM, and directory services don't talk to each other seamlessly, your AI is operating blind. Once your data layer is clean and accessible with Harmony, adding automation takes minimal effort.
the "60%+ auto-resolution within the first couple of weeks" number is the claim I'd want to poke at, that's a fast ramp for a helpdesk tool since most of the friction in IT support isn't the request itself, it's edge cases where the AI has to know when to escalate instead of confidently doing the wrong thing. what does the failure mode look like when an agent gets a request wrong, does it just get flagged by the employee or is there a way it catches its own uncertainty before acting on something like access changes?
agents that actually close IT tickets not just chat about them 👏 whats the false-positive rate looking like?