AI automation · Customer support automation
AI customer support agents trained on your business.
Generic AI chatbots (Intercom Resolution Bot, Ada, etc.) are templates. We build agents trained on YOUR product, YOUR docs, YOUR tone — that triage, draft, route, and resolve at the quality bar your brand requires.
What we build
First-response agent
Inbound ticket / chat → trained agent drafts a first response grounded in your docs + similar past tickets, resolves directly or routes to a human with context.
Triage + routing agent
Every inbound classified by topic, urgency, sentiment, and skill required → routed to the right tier-1 / tier-2 / specialist queue.
Voice support agent (optional)
For phone-heavy support orgs: trained voice agent on Vapi/Retell handling tier-1 calls, escalating warm to humans.
Macro + canned response generator
Continuous mining of past tickets → updated macro library + suggested canned responses for support reps.
Support ops dashboard
Custom command center: ticket volume, resolution rate, AI handle rate, escalation reasons, agent quality scores.
Default stack
- Claude (reasoning)
- Intercom / Zendesk / Front / Help Scout (support tool)
- Vapi (voice)
- Slack (escalation routing)
- Custom ops dashboard
Who this is for
SaaS companies and consumer brands with support ticket volume that's outgrowing the team but where the AI options on the market are too generic / too templated.
Questions
How is this different from Intercom Fin / Zendesk Answer Bot?+
Those are bolt-on chatbots inside the support platform. We build a custom agent trained on YOUR product, integrated across YOUR full stack (not just the support platform), with the ability to take real actions (issue refunds, update accounts, escalate intelligently). Different shape of product.
What about hallucination risk in customer support?+
Real concern, addressed by design. Agents only answer from grounded sources (your docs, your knowledge base, similar resolved tickets). When the agent doesn't have a grounded answer, it escalates instead of guessing. We build the guardrails into the prompt + retrieval.
Will customers know they're talking to AI?+
Your call. We can be transparent ("you're chatting with an AI assistant trained on Acme's product") or seamless. Most modern brands prefer transparent — customer satisfaction tends to be higher when expectations are set.
Other use cases