What working with us
actually looks like.

No black boxes. No surprises at handoff. We work transparently through four stages — and we don't consider anything finished until your team is genuinely using it.

01 Discovery call
02 AI Readiness Assessment
03 Build & implement
04 Adoption & handoff

Three things we promise
on every engagement.

🔍

We diagnose before we prescribe

We never arrive with a predetermined solution. Every engagement starts with understanding your business, your team, and your actual problem — before we recommend anything.

🤝

Your team is involved throughout

We don't disappear and reappear at the end with a finished product. The people who will use what we build are part of the process from the beginning — so handoff isn't a surprise.

We stay until adoption is real

Delivery is not the finish line. We measure success by whether your team is genuinely using what we built — confidently, consistently, and without us in the room.

Step by step,
start to finish.

Here's exactly what happens after you book a discovery call — no ambiguity, no jargon, no surprises.

1
30 minutes · Free · No commitment Stage one

Discovery call

This is a conversation, not a pitch. We listen to where your business is, what you're trying to solve, and what's held you back from moving on AI so far. By the end, we'll both know whether there's a fit — and if there isn't, we'll tell you honestly.

What we cover

  • Your business, your team, and your current operations
  • Where you see the biggest opportunities or pain points
  • What you've already tried, if anything
  • Your timeline and appetite for investment
  • An honest read on whether we're the right fit

What you get

  • A clear sense of whether AI is the right lever for your situation
  • Our initial perspective on where to start
  • A recommended next step — even if it's not us
  • No pitch deck, no follow-up pressure
2
1–2 weeks · Paid engagement Stage two

AI Readiness Assessment

Before we build anything, we need to understand what you're working with. We audit your operations, map your workflows, talk to your team, and identify where AI will genuinely move the needle — and where it won't. You get a prioritized roadmap, not a generic recommendation.

What we do

  • Operational audit — workflows, tools, data sources, pain points
  • Team interviews to understand how work actually gets done
  • Data landscape review — what you have and what's usable
  • Competitive context — where AI gives you the most leverage
  • Risk and compliance review for regulated industries

What you receive

  • A ranked list of your top AI use cases by impact and feasibility
  • A phased implementation roadmap with clear milestones
  • An honest assessment of build vs. buy for each use case
  • Team readiness report and adoption considerations
  • A fixed-scope proposal for Stage 3 — if you want to proceed
3
4–12 weeks · Scoped per engagement Stage three

Build & implement

This is where we build what we agreed to — on time, to spec, and with your team involved at every meaningful decision point. No vanishing acts. No scope surprises. We work in short cycles so you can see progress and course-correct early if needed.

How we work

  • Short build cycles with regular check-ins — typically weekly
  • Your team reviews and gives feedback throughout, not just at the end
  • We flag scope questions early, never at delivery
  • Documentation written as we build — not as an afterthought
  • Integration with your existing tools, not a replacement stack

What gets built

  • Custom AI models, automations, or analytics tools
  • Configured and integrated third-party AI platforms
  • Data pipelines and dashboards your team can actually use
  • Usage guidelines, governance docs, and admin controls
  • Training materials written for your specific workflows
4
2–4 weeks · Included in every engagement Stage four

Adoption & handoff

Most consultants call it done when they ship. We call it done when your team is using it — confidently and independently. This stage is built into every engagement, not offered as an add-on. It's the part that determines whether the investment actually paid off.

What we do

  • Live training sessions built around real use cases — not feature tours
  • Manager enablement so leadership can reinforce adoption
  • 30-day check-in to catch anything that isn't sticking
  • Usage tracking to identify gaps before they become habits
  • A clear handoff so your team owns what we built

What success looks like

  • Your team uses the tools without needing us in the room
  • Adoption is consistent — not just at launch
  • Your team can train new hires on the tools themselves
  • You can point to a measurable change in how work gets done

We don't consider
it done until you do.

Adoption is the hardest part of any AI implementation — and it's the part most consulting firms hand off to someone else. We build for it from day one, because a tool your team doesn't use is just an expensive experiment.

That's why Stage 4 is included in every engagement, not sold separately. It's not a premium add-on. It's just how we work.

Adoption is designed in, not bolted on
We think about how your team will use what we build from the first discovery conversation — not at delivery.
Your team helps shape what gets built
The people who will use the tools are involved in designing them. That's why they feel intuitive instead of imposed.
We stay for 30 days post-launch
Every engagement includes a 30-day check-in period. If something isn't working in practice, we fix it — no extra invoice.
We measure real usage, not just login counts
Logins don't mean adoption. We track whether the tools are changing how work actually gets done.

Things people ask
before they reach out.

Do we have to start with the AI Readiness Assessment, or can we skip to build?

If you already have a clearly defined problem and a specific solution in mind, we can scope a build engagement directly. But most clients who think they're ready to build discover important things in the assessment that change what they build. We'll be honest with you about which makes sense.

How long does a full engagement typically take?

It depends on scope and complexity. A focused automation build with a smaller team might run 6–8 weeks start to finish. A more complex custom AI build with broader organizational impact might take 4–5 months. We'll scope it clearly before you commit to anything.

We're a small company. Is this process right for us?

Yes — we scope every engagement to fit where a business is. For smaller companies, that often means a leaner assessment, a faster build cycle, and training that's calibrated to a small team. The process is the same; the scale adjusts.

What if our team is resistant to new technology?

That's one of the most common things we hear — and it's exactly why adoption is built into our process rather than treated as a training afterthought. We involve skeptical team members early, build for their actual workflows, and address concerns before they become blockers.

Do you work with companies that have no existing data infrastructure?

Yes. The assessment will surface what you have and what you need. Some of the highest-value AI work we do starts with getting the data foundation right — which makes every subsequent build faster and more reliable.

What happens after the engagement ends?

You own everything we build — the code, the documentation, the models. We provide a full handoff so your team can maintain and extend what we've built independently. For clients who want ongoing support, we offer retainer arrangements as well.

Step one is just
a conversation.

The discovery call is free, 30 minutes, and there's no obligation to move forward. We'll tell you honestly where we think AI could help — and if the fit isn't there, we'll say so.

Book your free discovery call

30 minutes · No commitment · Response within one business day