Zoona AI

Zoona AI builds customer-facing agents that ingest your knowledge base, documentation, and internal policies, then resolve inbound support requests autonomously around the clock. The core workflow: a customer submits a request, the agent retrieves relevant context from your uploaded content, generates a response aligned to your defined behavior rules, and either resolves the conversation or hands it off to a human agent with full context attached. The vendor describes this as resolution-driven rather than deflection-driven — the goal is a closed ticket, not a redirect.

The differentiating feature the vendor emphasizes is behavior control: you define explicit rules that govern what the agent can and cannot do, including the exact conditions that trigger a human handoff. For sensitive verticals — the vendor calls out financial services and healthcare specifically — this means the agent operates under guardrails backed by your own verified policy documents rather than general model knowledge. Escalations for fraud, security issues, or urgent patient cases route to the appropriate team with AI-generated context already attached, so the human picks up mid-conversation rather than starting cold.

Zoona AI fits teams that already have organized documentation and want to stop routing repetitive questions to human agents. It fits poorly when your knowledge base is fragmented or out of date — the agent sources answers from what you give it, and gaps in your docs become gaps in resolution accuracy. There is no self-hosted deployment option, which is a hard stop for teams operating under data residency requirements. Paid-only features gate some capabilities, so teams running purely on the free tier will hit ceiling before they hit production scale.