AI & Workflow Automation
We design and ship agentic workflows and RAG pipelines that take repetitive, judgment-light work off your team's plate — document intake, ticket triage, internal Q&A, reporting — built with the same infrastructure discipline as the network underneath it.
What We Build
"AI" covers a lot of ground. Here's specifically what we design, build, and operate — each one scoped to a real bottleneck, not a demo.
Ground a model in your own documents, tickets, and policies so it answers from what's actually true at your company — with sources, not guesses.
Agents that plan, call tools, and chain steps — document intake, ticket triage and routing, report generation — with confidence thresholds that escalate to a human instead of guessing.
Wire agents into the tools you already run — your CRM, ticketing system, billing platform, or internal databases — through clean, auditable API connections.
Scoped permissions, audit logs, and human-in-the-loop checkpoints on anything that touches sensitive data or takes an irreversible action.
Production deployment on AWS, GCP, or Azure with Kubernetes orchestration — built to run unattended and recover cleanly when something upstream fails.
Metrics and alerting so issues surface before a customer reports them, plus an ongoing feedback loop to tune accuracy as your data and edge cases evolve.
Set Expectations
A lot of "AI automation" pitches oversell. Here's where we think it genuinely helps — and where we'll tell you a simpler script or a process change is the better answer.
How We Scope an AI Project
We treat automation projects with the same rigor as infrastructure work: understand the system before changing it, document everything, and stay close after launch.
We sit with the people doing the work today to document the actual steps, exceptions, and systems involved — not the idealized version.
Before any model is wired up, we define what it's allowed to touch, what needs a human sign-off, and how we'll know if it's wrong.
We ship a working version against real data, running alongside the existing process until it's proven — not replacing it on day one.
Once live, it's covered the same as the rest of your stack — monitored, alerted on, and refined as your data and edge cases change.
AI and automation engagements are scoped and billed the same way as our other project work — by the hour, against a written estimate, or folded into a retainer once a workflow is live and needs ongoing care.
Get In Touch
Tell us what's repetitive, where it breaks, and what systems it touches. We'll tell you honestly whether automation is the right call — and what it would take to build it well.