Expertise

AI Support & Ops Systems

Ticket triage, agentic ops, and internal tools that let a small team behave like a much larger one.

Support is the highest leverage AI surface

Every growing business hits the same wall. Support volume climbs faster than hiring can catch up, quality slips, and founders end up back in the queue. AI is finally good enough to change that curve without pretending humans are out of the loop.

I build systems that sit between Freshdesk, an LLM reasoning layer, and a Supabase store of product knowledge. Tickets get classified, drafted, and enriched before an agent ever sees them. The human still ships the reply, but they start from a much better first draft.

Agentic, but accountable

The pattern I keep landing on is not a fully autonomous agent. It is an assisted operator. Every AI action is logged, every escalation goes to a human, every automated reply is traceable to the prompt version that produced it. That is what makes these systems safe to run in production for months.

Where this fits

This is a common entry point for teams that are curious about AI but not ready to rebuild their product around it. Start where the cost is obvious, prove the pattern, then expand.

Frequently asked
Will AI support replace my human team?+

No. The pattern that actually works is assisted operator: AI drafts, humans review and send. Volume and consistency improve, headcount usually stays flat while capacity grows.

Does this integrate with Freshdesk, Zendesk, Intercom, HubSpot?+

Yes. The core pattern is helpdesk agnostic. n8n handles the integration layer, so it works with any support tool that exposes a webhook or API.

How do you keep AI replies safe?+

Every AI action is logged, every escalation goes to a human, every automated reply is traceable to the prompt version that produced it. Nothing is sent without a review step for the first months of any deployment.

Estimate the impact

Move the sliders. See the shape of the numbers.

A first pass calculator for this practice area. Useful for the first budget conversation, not a quote.

Estimate the deflection

See how much a support triage layer buys back.

Move the sliders. See hours reclaimed once an AI layer classifies, drafts, and enriches tickets before a human replies.

220 tickets
202,000
9 min
330
45 %
1570
// results, recomputed live
  • Agent hours reclaimed327 h / mo
  • Draft coverage on inbound45%
    Classify, enrich, and draft before a human sees it
  • System run cost£138 / mo
    Claude plus n8n plus Supabase
  • Headcount equivalent2.2 FTE

The point is not to remove humans. It is to give the ones you have a much better first draft on every ticket.

Other pillars

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