The inbox triage, the chasing of confirmations, the re-typing of the same data into the CRM. We map where those hours go, put a number on them, and build AI systems inside your existing tools to take that work over.
Every square below is an hour you pay for: salary, software, overhead. Most founders who look at where those hours actually go don't like the answer.
Each square is one hour of one person's week. You pay for all forty. The question worth asking is how many of them go to work that actually needs a person.
Answering the same questions, chasing confirmations, moving data from the inbox into the CRM, assembling the Friday report. Ask your ops lead how much of the week that eats. Most say around a third, and it grows with volume.
We build AI agents and automations that pick this work up the moment it appears, including at 2 am, inside the tools you already run. Anything ambiguous goes to a person with full context, because an escalation is always better than a bad response.
What's left are the hours that need judgment: the client calls, the exceptions, the decisions. Same team, same payroll, pointed at work that grows the business. And when volume doubles, the system absorbs it instead of your headcount.
If you've tried automation before and it didn't stick, the tool probably wasn't the problem. Most automation fails because someone bought software before understanding the work. If the process isn't standardized before AI touches it, you're automating inconsistency, so we start with a map.
A fixed-fee mapping sprint. Interviews and walkthroughs with the people doing the work, about three hours of your team's time total, until we know how the operation actually flows rather than how the org chart says it does. If the honest answer is that a process needs fixing before AI touches it, that goes in the report.
A fixed quote, signed off before any work starts. We build inside the tools you already run, your CRM, your helpdesk, your inbox, so nobody on your team has to move platforms. Every agent ships with an escalation engine, because an escalation is always better than a bad response.
The operation you mapped in month one won't be the one running in month nine. A monthly retainer covers monitoring, tuning, and new workflows as they earn their place on the roadmap. You own everything from day one, so you can take it in-house whenever you want.
The largest of these handles 40%+ of support tickets for operators managing 5,000+ units, with first response down from over a day to under 2 minutes. Every system here runs inside the tools the team already used. Open a card for the numbers.
Helped deploy an AI system for property management ticket handling across 5,000+ units. 40%+ of tickets automated, response time under 2 minutes.
Read the full case→Helped build a full AI home maintenance platform from concept to production. A text-based concierge that knows everything about your home and keeps it running.
Read the full case→Voice AI that picks up every after-hours call, qualifies patients, and books consultations. Now running across roughly 8 cosmetic medical practices.
Read the full case→PathCubed is a small AI engineering studio in Lisbon. Every engagement is fixed scope with named deliverables, and we stay on until the system holds up under real volume. Below, what we do and how we work.
Operations interviews, process mapping, ROI modelling. We figure out what's worth automating before anyone writes a line of code.
LLM agents, multi-step workflows, retrieval, evals. Built against your real SOPs, not a generic template.
CRMs, helpdesks, billing, custom APIs, internal databases. The plumbing that makes the AI part actually useful.
Monitoring, cost controls, edge-case QA, runbooks, team training. Systems that survive past the demo.
Usually that's because someone bought a tool and tried to plug it in without understanding the full workflow. We spend two weeks mapping everything before we touch any automation. It takes longer up front, but the thing actually works when we're done, and your team isn't the one holding it together with duct tape.
Around three hours of your team's time in the first phase, interviews and walkthroughs so we understand how things actually run. After that we handle the build. You'll see working demos every week, but the work isn't landing on your team's plate.
Mapping takes two weeks. Build runs four to twelve weeks depending on scope. Most clients start seeing the difference within 90 days of going live. The first thing most people notice is how quiet their inbox becomes.
Then we'll tell you. The audit is a fixed-scope, fixed-fee piece of work whose output is useful whether or not you proceed. If the honest answer is 'fix the process before you automate,' that's what goes in the report.
You own everything. Code, infrastructure, credentials, data, all in accounts you control, from day one. We operate inside your environment, not on top of it behind a black box.
Thirty minutes on a call. You describe how the work flows today, and we tell you which parts are automatable, which aren't yet, and roughly what each is worth. If the honest answer is to fix a process before adding AI, you'll hear that too.