Use case
AI customer support automation
Deflect tier-1 tickets, auto-route tier-2, and free your human team for complex work.
Overview
A retrieval-grounded support agent that answers from your help docs, past tickets, and product data. Automatically escalates to humans with context attached. Works across email, chat, WhatsApp, and in-app surfaces.
Key questions we answer during scoping
- How do we prevent the AI from making confident-sounding wrong answers?
- What happens when the AI doesn't know? (hand-off UX, context passing)
- How do we measure savings without breaking customer trust?
- How do we keep it current as product changes?
Reference timeline
6–10 weeks
Investment
$60k–120k
Best for
- 5,000+ tickets per month
- Repeat question patterns
- Existing knowledge base
Typical outcomes
What shipping this looks like.
58%
ticket deflection
1.2s
avg response
-$2.1M
annual support cost
Reference stack
The typical tools for this use case.
Every engagement picks the right tool for your context — these are defaults, not prescriptions.
OpenAI GPT-4oPineconeZendesk APIIntercomTemporal
Related services
Services that deliver this use case.
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/ Next step
Thinking about ai customer support automation?
Book a 30-minute scoping call. We'll tell you what shipping this looks like for your context.
~4h
avg response
Q2 '26
next slot
100%
NDA on request