Hunter Douglas uses Decagon AI agents across markets. Decagon reports 40% average deflection, more than $1 million in revenue from conversations handled fully by AI, and 85% higher average order value among customers who engaged an agent.
Reported outcomes
Outcomes are reported exactly as stated by the source; we have not independently audited them.
How it works
- Decagon AI agent answers inbound customer conversations.
- Escalates to human agents when needed.
Risks & compliance
- Incorrect answers to customers; escalation paths needed
- Vendor-published results; not independently audited
Tools mentioned & how to build it
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Tools mentioned
- Decagon (Decagon)
AI customer-support agents for chat, email and voice.
Build a version yourself
- n8n
Open-source workflow automation with AI agent nodes; self-host or cloud. - HubSpot (Breeze agents)
SMB-friendly CRM with Breeze AI agents for prospecting and support. - Relevance AI
Build an 'AI workforce' of agents, e.g. BDR agents that research and book meetings.
Sources
“Additionally, more than $1 million in revenue has already come from conversations fully handled by AI, without ever being escalated to a human.”Hunter Douglas and Decagon
Grade rationale: Named organization with a quantified outcome from the vendor or the organization itself (self-reported). Automated check on Oct 17, 2026: 1/1 quotes and 3/3 outcome claims matched the source. Compiled by the Agent Casefile research desk (AI-assisted; see methodology). Spot an error? Request a correction.
