Everyone's adopting AI. Almost no one has the time to roll it out right.
Every company knows it needs AI. The pressure is everywhere, and it's real. But wanting it and actually rolling it out across a busy business are two different problems, and almost no one has the time to do it properly, responsibly, and at scale. So teams buy licenses, run a workshop, and hope. A few months later the tools sit unused and the promised hours never show up.
Training without a workflow
People learn what AI can do, then go back to doing the work the old way. Nothing in the day-to-day actually changes.
Generic setup, no fit
"Here's ChatGPT, go nuts" isn't an implementation. Without your context, templates, and data loaded in, output is mediocre and trust erodes fast.
Nothing that runs
The painful steps are still manual. No tool, no automation, no measurable hours saved, just a more expensive version of the same process.
Every engagement ships the same box.
Six things land in your environment by the end, configured, documented, and working. It's a product, not a custom scramble, and not a deck of recommendations you have to go implement yourself.
A live configured workspace or tool
A configured AI workspace or tool running in your own environment, loaded with your context, templates, and data, with tuned instructions. A purpose-built station, not a blank chat box.
Workflow SOPs with the AI step baked in
The step-by-step an employee actually follows: which steps are human, which are AI, and the before → after. This is what makes it stick after we leave.
A prompt & template library
The recurring work, pre-built. Your team reuses proven prompts and templates instead of starting from scratch every time.
Recorded + live training
A recorded walkthrough your team keeps for onboarding, plus a live champion session so the people doing the work can run it without us.
A handoff & governance one-pager
How to keep this running once we're gone: ownership, guardrails, and what to do when something changes.
A before/after time estimate
A concrete read on the hours this gives back, e.g. "~6 hrs/wk → ~1.5 hrs/wk" on the target process, so the value is measured, not assumed.
You get a real working thing. Not a slide deck.
Most AI consultants can only train. I ship working tools.
Anyone can run a workshop. The hard part (and the reason a process actually gets faster) is building the custom tool behind the button an employee presses. I've already shipped three production apps, including the exact kind of reorder tool a build engagement delivers.
Evolve Inventory
A multi-tenant inventory and reorder platform for retailers whose POS can't handle the multi-vendor reorder workflow they actually need. A clerk opens one screen ("reorder these SKUs, here's why") and clicks approve. This is precisely the "custom tool behind a button" a build engagement ships, running live with a real customer.
It handles daily ordering across 20+ vendors and 800+ SKUs, with reorder calculations driven by sales velocity and vendor turnaround. Live in production with our first customer, an independent retailer whose parent franchise operates 450+ locations across the U.S.
Evolve App
A full production web app that tracks patterns, builds self-awareness, and guides growth through structured AI sessions. 35+ build sessions, live in production.
Read the case study →Diamond Data
A data product with a custom scoring model and a daily multi-source pipeline (MLB, Statcast, weather) feeding a live dashboard. Proof I can wrangle messy data into something useful.
Read the case study →LicenseHub
A full demonstration build (marketing site, interactive dashboard, and a working AI advisor) showing how I take a concept to a complete, polished product.
Read the case study →From discovery to handoff in 2–4 weeks.
That's elapsed calendar time, not a month of meetings. Your team is involved at the front and the end; the heavy build in the middle is heads-down and on me.
Discover
We map the target process, find where the hours actually go, and agree on the before/after we're aiming for.
Build
I configure the workspace, write the SOPs, and build the custom tool, async and controllable, with check-ins.
Train
A recorded walkthrough plus a live champion session, so the people doing the work can run it confidently.
Hand off
You keep the working system, the docs, and a governance one-pager, plus the before/after time estimate.
Three tiers, by company size.
Same box, different scope: one workflow, a whole department, or a full org rollout. Most engagements land in the middle tier.
- One configured workflow + its SOP
- Prompt & template library for that process
- Recorded + live training
- Handoff one-pager + before/after estimate
- No custom code
- Multiple workflows configured end to end
- One custom internal tool built around your process
- Champion training + recorded walkthrough
- Prompt library, SOPs, governance one-pager
- Before/after time estimate on each workflow
- Multi-department rollout
- Governance & champion networks
- Measurement dashboard
- Multiple custom tools as needed
- Scoped engagement, custom pricing
Fixed scope, fixed price. Anything beyond the box is a change order or the next engagement.
One builder, accountable end to end.
Evolve Labs is run by Matt Morris: fifteen years of high-stakes client work, a year embedded inside real business operations as an implementation consultant, and a portfolio of production apps shipped with AI as a technical partner. You work with the person doing the building, not a handoff chain.
Have a process worth fixing?
Tell me the one workflow that eats your team's week. If it's a fit, I'll scope it and we'll have a working system in 2–4 weeks.
Book a call →