AI use case delivery
Lakely finds the work AI can take off your team's plate, then builds it into the tools they already use.
1Where to start
We’ve seen where AI pays off in businesses like yours, so we show up knowing how the work runs. What we build is shaped around your team.
A CRM that fills itself in from email and calls.
Credit memos drafted in an afternoon, gaps flagged.
Same-day quotes, priced from your own job history.
Prior auth packets matched to each payer's criteria.
A one-page brief for every manager before doors open.
Scope creep caught while it can still be billed.
Struggling students reached in week four, not week twelve.
If your team does it every week with email, documents and a system of record, it's probably a candidate.
2By role
Your team gets back the hours they spend on busywork. You get a result you can take to the board.
A close that finishes sooner, and a clear line from AI spend to the result it bought.
Fewer handoffs, shorter queues, and the same output from a team that isn't working weekends.
AI built inside your stack and permissions, so your team doesn’t learn another tool. You own all of it.
Reps selling instead of updating the CRM, and a forecast that explains itself.
Campaign reports drafted for you each week, and every lead followed up before it goes cold.
Policy questions answered in seconds, and onboarding that doesn’t depend on one person’s inbox.
Every department has a process that eats the week. Let’s find yours.
3The gap
Most companies bought the tools, ran a pilot, and watched usage fade. What’s missing is someone who picks the right job for AI, builds it into how work gets done, and answers for the result.
of businesses say they need an outside partner to get real value from AI
of CEOs have seen no real financial benefit from AI yet
In our experience, the companies seeing a return have a partner who answers for the result. Lakely is that partner.
4How we decide what to build
Most processes exist because they made sense once. The weekly report was weekly because someone needed it on Mondays in 2019. The approval had three sign-offs because of one bad discount. AI changes how much effort a task takes, so it's worth asking whether the task should still look the way it does.
1
Who uses this work, and what do they do with it?
2
What have we watched happen, and what are we only assuming?
3
If we started from scratch, what would still need to happen?
4
How will this move the number we care about?
5
When would this be the wrong call?
If a use case can't answer all five, we don't build it. Sometimes the right fix is a formula, a short script or a setting in software you already pay for. We'll tell you that too, even though it's a smaller invoice.
See our approach5How we ship
First use case live in about 90 days.
6Why Lakely
Our AI engineers spend time with your team first, learning how the work runs, then build alongside the people who’ll use it.
After launch, we train your team, watch how it’s used, and keep tuning it until it’s part of the routine.
AI drafts, flags and recommends. Anything going to a customer, patient or regulator gets reviewed by your team first.
A consultancy usually ends with a recommendation. We end with a working tool your team uses every day, and a scorecard showing what it changed.
A product does one thing the way its vendor designed it. We build around how your work gets done, inside the systems you already run, and you own what we build.
The one with the clearest payoff, the data you already have, and a team that wants it. Finding that is the job of our first phase, Map. Our industry examples give you a head start.
We’re model-neutral. We pick the model that fits the job, your security requirements and what it will cost to run, and we can build on the AI tools you already license.
No. We bring the AI engineers. You bring the people who know the work and an hour a week to tell us when it's right.
You do. The code, the prompts, the configuration and the documentation are yours.
We build in your environment, under your access controls and compliance rules. Your data can stay in Canada.
Every phase has a fixed scope and a fixed price, agreed before we start.
Book a use case session
Sit down with a Lakely AI engineer. Bring one process that eats your team’s week. You’ll leave knowing whether AI is the right fix, what it would take to build, and what it could return.