Applied AI & Automation
Not a demo, not a chatbot bolted onto your website. We build and run AI on the operational work that eats your team's time (support tickets, security findings, routine requests) with guardrails, validation, and a person accountable for every consequential action.
The problem we own
Tickets, alerts, and routine requests pile up. Good people spend their day triaging instead of solving.
An impressive demo stalls the moment it meets real data, real edge cases, and the question "who's accountable when it's wrong?"
AI adopted in pockets makes confident mistakes with no review step, no audit trail, and no owner.
Usage-based AI spend grows quietly until it shows up on a bill nobody forecast.
What we actually do
We put AI on well-scoped, high-volume work and keep a human on every decision that carries consequences. The typical shape is a first-responder for your operational queue: read, diagnose, draft, route, and notify, with a person approving the trigger.
A person approves every consequential action. The AI never acts on its own.
We're explicit about the line between experimental and production-ready. If a use case isn't reliable enough to trust, we'll tell you, and we won't ship it as if it were. Anti-hype is the point.
Discover, ground, pilot, measure, harden. A typical engagement starts with a fixed-scope assessment of where AI actually pays off, grounds a pilot in your data, measures it against a validation set, and only then hardens it for production. Urgent operational pain can start immediately, assessed in parallel.
See how engagements start
Proof
As part of a security-program rebuild, we deployed AI agents against a rebuilt knowledge base to triage and draft help-desk responses, cutting resolution time 35%, with staff reviewing and approving before anything reached a user.
Read the full case studyContact
Tell us where the volume is piling up. We'll tell you honestly whether AI is the right answer, and where it isn't.
No sales funnel. No lead pipeline. Confidential.