Helpdesk Automation

Helpdesk automation for the queue that never empties.

We build AI agents that triage, route, and resolve the repetitive tickets in your queue — on your rules, inside the helpdesk you already run — so only the tickets that need a person reach one.

  • AI implementation services
  • AI agents in your cloud
  • Your triage rules, encoded
  • Only exceptions reach a person

Built with the leading AI platforms

NVIDIAAnthropic
Peter Enestrom, founder of Zaigo

Led by Peter Enestrom and the Zaigo AI & engineering team

YaleColumbia UniversityMicrosoft

The broken Friday

Ticket deflection was the promise. The queue kept growing.

From support leaders we have sat with: operators at PE-backed workforce platforms, where 109 VMS integrations mean the queue speaks a hundred dialects and every repetitive ticket still lands on a person.

  • The queue speaks 109 dialects

    Every VMS integration, client portal, and worker population sends its own kind of ticket. All of that variety lands on the support team as one undifferentiated queue.

  • The same ticket, answered again

    Status checks, document chases, "where is my…" questions — a trained person re-typing an answer the company has already written hundreds of times.

  • Triage is one of twenty jobs

    Your support leads carry twenty different tasks in a day; reading and routing the queue is one of them. It happens when there is time — and there usually isn’t.

  • The AI tool the team routes around

    The last automation promised deflection; it shipped generic answers that didn’t know your clients, your VMSs, or your escalation rules — so agents learned to work around it.

  • Change management is the blocker

    The team has fallen down the adoption hole a few times: a tool rolls out, nobody changes how they work, and the queue comes back. The tech was never the hard part.

What manual costs

An AI ticketing system is a headcount decision, not a software one.

What the manual way looks like at a platform supporting workers and clients across 109 VMS systems. Your numbers will differ — tracing one week of the queue puts figures on yours before anything gets built.

109VMS systems feeding the queue at one workforce platform — each client population with its own ticket shapes
20Tasks in a support lead’s day — reading and routing the queue is one
Every shiftThe queue refills with tickets someone has answered before — the repetition, not any single ticket, is the cost

From an anonymized engagement — a PE-backed workforce-management platform integrating 109 VMS systems

How it works

Service desk automation that encodes your rules.

No new system for your team to learn. The triage your best support lead would run on every ticket becomes the system — AI agents run it inside the helpdesk you already have, and people handle the exceptions.

  1. 01

    Trace one week of the queue

    We follow a week of tickets from arrival to resolution — which ones repeat, which rules your best people apply, where tickets bounce between teams.

    Weeks 1–2
  2. 02

    Encode the rules

    Triage logic, escalation paths, client-specific handling, VMS lookups — documented with your support leads and encoded as rules you own.

    Yours to keep
  3. 03

    AI agents work the queue

    Every incoming ticket is classified, routed, and — when the answer is known — resolved on the spot; anything that breaks a rule lands with a person, the reason attached.

    Every ticket
Not another license

Freshdesk AI vs. a system built on your rules.

Freshdesk’s built-in AI is genuinely good at what it is built for: generic deflection, drafted replies, a smarter search bar. What it cannot know is your triage logic, your escalation paths, or which of your 109 VMS systems a ticket is actually about.

We build AI agents that run inside the helpdesk you already pay for, in your cloud, on rules encoded from how your team actually works. You own the IP; only the tickets that need a person reach one, with the context attached.

Peter Enestrom, founder of Zaigo
Who builds it

Led by Peter Enestrom.

Co-Founder — leads AI & Engineering

Pete Enestrom

Every engagement is led personally by Pete, working with the Zaigo AI & engineering team from the two-week audit through the production handover. The person who scopes the work is the person who builds it.

Education
Yale & ColumbiaGraduate
Background
Microsoft & IntelFormer
Experience
Exited FounderVenture-Backed

Background

Questions

Asked by support and operations leaders.

The straight answers, before you book anything.

What’s holding your business back?

A workflow ready for automation. An AI product you want to build. A problem that has sat on the roadmap for years. Let’s talk about what it would take to solve it.

Talk to Zaigo