AI Consulting & Automation
We don't pitch AI. We deploy it.
UTS builds production-grade AI systems that run real businesses, anchored by CaptivaHQ, our AI-powered Enterprise Operating System, and AccessIQ, the fastest way to add AI to what you already run. Both powered by Atlas. Free proof of concept on your real data.
The Products
Two platforms. One intelligence layer.
CaptivaHQ runs the whole business. AccessIQ adds AI to the one you already run. Atlas powers both.
CaptivaHQ
The AI-powered Enterprise Operating System.
A CRM tracks contacts. An EOS runs your entire operation. CaptivaHQ replaces a stack of disconnected tools with one platform where every module shares a single Knowledge Base. Atlas answers across all of it.
What makes it different
Everything it runs
LiveRunning in production with Poma Architectural Metals, Alliant, CAC Vibe.
- Dana asks Atlas: “What needs me today?” Atlas answers: “3 overdue, 2 deals at risk, 4 meetings” and her My Day dashboard highlights the task “Find new leads”.
- Dana runs AI prospecting with the brief “Water utilities · Southeast · 100–500 staff”. It returns 3 leads — Coastal Water Authority, Blue Ridge Regional Water, and Tidewater Municipal Utilities — and she selects Coastal.
- Atlas says: “Drafting a branded proposal and email now” and produces a $44,400 / 240 hour proposal plus a matching outreach email: “Pulled the scope, quote, and contact from the deal.”
- The deal is won. Atlas: “Deal won. Spinning the project up from your template. Hours, budget, and three roles carried over” — roles, allocations, and a schedule appear.
- Predictive health flags the budget: Atlas warns “At current burn, budgeted hours run out ~Nov 12 — three weeks early” and recommends “Rescope Phase 2 by 40 hours and you land on budget.” The budget returns to green.
AccessIQ
Add AI to what you already run.
A secure portal your clients and team log into to see reports, billing, work orders, and documents, with Atlas built in to answer questions over that data. White-label ready, role-based, live in days.
- The AccessIQ orb sits at the centre. Around it, an HVAC contractor’s six systems appear, none of them talking to each other — ServiceTitan, QuickBooks, CallRail, Podium, Sortly, and Google Drive. Six systems, zero shared context.
- AccessIQ connects all six to the orb — five through API tools, Google Drive as a knowledge base. Status flips to systems connected, and live context starts flowing.
- Priya asks: “Is the Rooftop 4 compressor still under warranty — and did we already bill the last visit?” One question that spans three of those systems, which light up as she names them.
- A live canvas forms beneath the question — a card for the last visit from ServiceTitan, the warranty from Google Drive, and billing from QuickBooks — each filling with what its system returned.
- The canvas condenses into three source citations as Atlas answers: “Yes — warranty runs through 03/2027. The last visit was invoiced 11/18 and paid.” — sourced from ServiceTitan, the warranty PDF in Drive, and QuickBooks.
- A new document, 2026-WARRANTY-TERMS.PDF, drops into Google Drive and is indexed. Priya asks “Does that cover the compressor coil?” and Atlas answers “Coil is covered — parts and labour, under the 2026 terms.” — citing the new document.
C3POperator
An AI receptionist that answers every call — and gets the work done while it's still on the line.
It talks with your callers in real time, recognises returning customers, answers from your own business knowledge, and books appointments straight into your calendar — then texts and emails the confirmation.
It only works with what you give it access to — your customer records, your knowledge base, your schedule — so every answer is grounded in your business, not guesswork.
When a call needs a person, it transfers the caller to your team with the full context of the conversation.
- A call comes in from a known number. C3POperator answers in 0.4 seconds and, before anyone speaks, pulls up the caller’s customer record from its Data Tables: Elena R., returning, 2019 CR-V, last visit in March for brakes. The agent speaks first: “Hi Elena — thanks for calling Harbor Auto. How can I help?”
- Elena: “The brakes are squeaking again. Can someone look at it this week?” The last-visit row lights up, and the knowledge base returns the brake warranty: twelve months. The agent: “Your March brake job is still under warranty, so the inspection is free.”
- The agent checks this week’s calendar: most slots are taken, two are open. “I have Thursday at nine or Friday at two. Which works better?” Elena: “Thursday at nine, please.” Thursday at nine is booked during the call.
- One confirmation goes out by text and email. The agent: “You’re all set for Thursday at nine — I just texted and emailed the details.” Elena: “Perfect, thank you!”
- The call ends after 1 minute 48 seconds. The agent keeps working: it writes the next visit — Thursday at nine, under warranty — into the customer record, adds a call summary, and marks the record updated. The frame holds two seconds before the loop replays.
UTS Chat
A private AI workspace for teams — private models, and nothing you write is used to train AI.
Chat with leading models, work with your files and company knowledge, research the web, and build agents — in one workspace your whole team can use. Invite people by email and manage every license from settings.
Prompts run through private models with no training on your data. Team licenses and data controls stay under your organization’s control.
- Katrin, Head of Operations at Nordwerk Logistik, opens Team settings in UTS Chat: 4 of 10 licenses in use. She clicks Add users, enters three colleagues’ email addresses and sends the invites. Three rows show Pending; the counter reads 7 of 10 licenses.
- She opens a new chat and picks a model from the selector, which then reads “Qwen 3.8, Private models”. The view zooms to the flag and back.
- She attaches supplier-agreement.pdf, 14 pages, encrypted on upload, and asks: “Check this supplier contract against our procurement policy. What should legal see first?” UTS Chat extracts the content, then deletes the file, and pulls in the company’s procurement policy. The answer, “3 clauses for legal, by risk”: Liability cap: 1× annual fees — your policy requires at least 2×; Auto-renewal: 90-day notice — policy maximum is 30 days; Data processing: no DPA attached — ask the supplier before signing. Sources: the contract (sections 7, 12 and 15) and the procurement policy.
- She replies “Thank you!” and the workspace clears to a heading, Your data is private, and two statements: Zero retention at the model provider. Your data is not used for training. The frame holds two seconds before the loop replays.
Choose Your Path
Two ways in. Pick yours.
Whether you're ready to replace the stack or just want AI on top of it, there's a clear starting point.
Replace your stack
CaptivaHQ: one AI-native system that runs the whole business.
- You run 5+ disconnected tools and want one system
- You're ready to consolidate CRM, projects, finance & support
- You want AI built into operations, not bolted on
- You have leadership buy-in for real change
Keep your systems, add AI
AccessIQ: Atlas intelligence on top of what you already run.
- Your current tools work. They just don't talk to each other
- You want AI answers over your existing data
- You need a client-facing portal in days, not months
- You want to start small and scale from there
How It Works
From first call to full deployment
A simple, transparent process designed to get you results fast, with zero risk upfront. You don't pay until you've seen it work.
Discovery & Assessment
We start by listening. In a focused session, we map your current workflows, identify bottlenecks, and understand the outcomes that matter most to your business.
No jargon. No pressure. Just a clear picture of where you are today.
AI Opportunity Mapping
Our team translates your challenges into a prioritized roadmap of AI opportunities, ranked by impact, feasibility, and speed to value.
You'll see exactly what's possible and what to tackle first.
Proof of Concept
We build a fully functional proof of concept, at no cost to you, using your real data and systems. You see measurable results before committing to a full rollout.
Production-ready AI that drives real efficiency gains, automates critical workflows, and empowers faster decisions. Delivered free, so you can evaluate with zero risk.
Implementation
Our engineers deploy the full solution with minimal disruption to your team. We handle integrations, training, and go-live. End to end.
Your staff gets onboarded. Your systems get upgraded. You stay focused on your business.
Optimization & Support
After launch, we monitor performance, gather feedback, and continuously improve. Our team is always available, not just on day one.
Ongoing partnership, not a handoff.
Review before you pay. Guaranteed.
You receive the full working proof of concept, evaluate it against your real workflows, and only move forward if you're satisfied. No invoices, no obligations until you decide to proceed.
What Clients Say
We let the work speak first
Every quote below is from a client running production AI we built, and using it daily.
“UTS built us an Executive Dashboard that changed how we see our business. We went from pulling reports manually to having everything we need in one place, in real time. It's become something our leadership team relies on every day.”
Jonathan B.
Chief Financial Officer · Alliant Property Management
“UTS meets us where we are. They build on the systems that run our business instead of ripping them out, their team is in the room with our crew every week, and what our crew raises turns into what they build. Visibility into our operations that we did not have a few months ago is on demand today, with more coming online in phases. That is how you modernize a company that has been at this since 1969.”
Daniel F.
Chief Executive Officer · Condition Analyzing Corporation
Trusted by teams running our AI in production
The Problem
AI is everywhere. Deployed AI isn't.
Every vendor is pitching AI. Very little of it survives contact with real data, real workflows, and real teams. Here's what businesses are actually up against.
The average mid-market company runs its operation across 10+ tools that don't talk to each other. Nobody sees the whole picture.
Most AI initiatives stall at the demo stage. They look great in a slide deck and never make it into daily operations.
Hiring your own AI team runs close to a million dollars a year, before a single system ships.
The Math
What AI actually costs: in-house vs UTS
Building an internal AI team is the most expensive way to find out what works. We've already made the mistakes on our own dime.
Typical fully-loaded annual cost
Hiring an in-house AI team
- Senior AI/ML engineer$215K
- Data engineer$170K
- MLOps / infrastructure engineer$185K
- Recruiting & ramp-up$95K
- Benefits & payroll overhead$170K
- Cloud, GPU & tooling$120K
Senior engineers, production systems
Deploying with UTS
- Free proof of concept on your real data
- Senior engineers, no offshore handoffs
- Live in production in ~30 days
- A fraction of the cost of a single hire
Start free. Pay only when you've seen it work
Schedule Free ConsultationLet's Build Your AI Advantage
Stop wasting time on manual processes and disconnected systems. Let's identify exactly how AI can improve your business, before you spend a dollar.
“AI that actually works in your business.”·“From idea to automation. Fast.”·“We don't pitch AI. We deploy it.”