Curology, a D2C prescription skincare company that has treated nearly 6 million patients, uses Decagon AI agents for support. Decagon reports chat rising from 5% to 80% of ticket volume and support operation costs cut by 65%.
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
- Health information; clinical questions must route to clinicians
Healthcare cases cover operational and commercial workflows. Nothing here is medical advice or a claim about a device's or drug's efficacy.
Tools mentioned & how to build it
Disclosure: Some links may earn us a commission; it never affects grades. Tools are listed by fit to this case, never by payment.
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
“Since implementing Decagon, Curology has significantly reduced customer support operation costs by 65%.”Curology 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 2/2 outcome claims matched the source. Compiled by the Agent Casefile research desk (AI-assisted; see methodology). Spot an error? Request a correction.
