AI agents for customer service
The honest position: customer service is the most mature agent category there is, and per-resolution pricing has standardised around $0.99–$2.00 per resolved conversation — Intercom Fin at $0.99/resolution, Zendesk AI at ~$1.50–$2.00/automated resolution (Intercom, 2026; Getmacha, 2026). If your need is standard ticket deflection, buy a platform — you will not beat that economically with a custom build, and we’ll tell you so.
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When to buy a platform instead of hiring us
Read on if your service operation isn’t standard.
- Your volume is email and web chat on common questions
- Your knowledge base is already good
- You’re deflecting tier-1 tickets, not completing transactions
- You have no unusual systems in the loop
Intercom Fin, Zendesk and HubSpot Breeze all do this well. Go and buy one.
When a custom build is the right call
- Your workflow crosses systems the platform can’t reach. Deflection is easy. Completing the transaction — checking real availability, raising the work order, releasing the credit — requires reaching your systems of record.
- The phone is your primary channel. Most platforms are text-first with voice bolted on. If most of your volume is calls, that’s a different build.
- Your domain knowledge isn’t in a knowledge base. It’s in an ERP, a permit system, a property management platform, or in the heads of people who’ve been there fifteen years.
- You’re regulated. Where an answer creates liability, deterministic logic and approval gates matter more than fluency.
What we’d build
- Voice agents for the calls currently going unanswered
- Workflow agents that complete the transaction rather than describing it
- Escalation design that hands over with full context — the difference between an agent people trust and one they route around
- Evaluation infrastructure, so you can prove quality rather than assume it
The metric most teams get wrong
Deflection rate rewards the wrong behaviour. An agent that deflects 80% of contacts while resolving 40% is destroying your customer experience efficiently.
Measure resolution rate, escalation rate with reasons, and contacts avoided upstream. We build reporting around those three from day one.
Frequently asked questions
We already have a chatbot. Is this a replacement?
Often it’s a layer above it. The chatbot handles FAQ; the agent handles the transactions it currently can’t.
How do we prove it’s not making things worse?
Shadow mode, then staged rollout, with a regression suite running continuously. If quality drops, you see it in the monthly report before a customer tells you.
Will this reduce headcount?
Usually it changes what the team does rather than how many there are — routine volume falls, escalation quality rises. If your goal is explicitly headcount reduction, say so in the audit and we’ll model it honestly.
Your industry changes the answer
The same function looks different in a dealership, a venue and a contractor. The audit maps yours specifically.