AI consulting that ends with a costed build plan
Two weeks with your operators and your data, and you walk out with ranked use cases, real numbers, and a sequence you can actually fund and staff.
How it works
Most AI strategy work ends with a maturity model and a list of themes nobody can budget against. Ours ends with a spreadsheet: every candidate use case, the hours it consumes today, what it costs to build, what it saves, and what has to be true about your data before it will work. We spend the two weeks with the people doing the work rather than the steering committee, because that's where the actual numbers live. Then you decide what to fund, with us or with anyone else.
Two-week discovery, not a six-month study
A small senior team goes deep on your operations fast, so the roadmap lands while the budget cycle is still open.
- Operator interviews and live process shadowing
- Data and systems audit across your core platforms
- Draft findings reviewed with you at the halfway mark
- Fixed fee, fixed dates, no scope drift
Every use case costed and ranked
You get build cost, expected savings, payback period, and technical risk for each candidate, so prioritization stops being a debate.
- Hours and cost baseline per process, measured not guessed
- Build-versus-buy call on each item with reasoning
- Sequenced 12-month roadmap with dependencies mapped
- Vendor-neutral: we'll tell you when an off-the-shelf tool wins
Readiness on data, security, and governance
The honest assessment of what will block you, from data quality gaps to the approval policy your legal team hasn't written yet.
- Data quality and availability scored per use case
- SOC 2 and regulatory considerations flagged early
- Draft AI usage and human-review policy for your teams
- Skills gap and staffing plan for running it after launch
Where teams use it
Built for real revenue work.
Where do we start with AI?
A leadership team with budget approved and no consensus on the first project. Discovery surfaces the fifteen candidates hiding in operations and ranks them, so the first build is chosen on payback rather than on who argued hardest.
Build, buy, or platform?
You have quotes from a dev shop, a SaaS vendor, and an internal team all claiming the same outcome. We evaluate each against your actual data and integration reality and give you a defensible recommendation with the total cost of ownership attached.
Rescuing a stalled AI program
Pilots that impressed everyone in the demo and never reached production, usually because of data access, evaluation, or ownership gaps. We diagnose what stopped them and lay out what it takes to get one into real use.
“We'd already paid a large firm for an AI strategy and got sixty slides we couldn't act on. APPIT gave us eleven pages with a cost and a payback number next to every idea, and we had the first project funded within a month.”
FAQ
Questions, answered.
How much does AI consulting cost?
Our standard two-week discovery sprint is a fixed $18,000 to $35,000 depending on how many business units and systems are in scope. Larger multi-entity assessments run higher and take three to four weeks. If you go on to build with APPIT, the full discovery fee is credited against the project, so the strategy work effectively costs nothing when it leads to a build.
What do we actually receive at the end?
A ranked use case register with build cost, projected savings, payback period, and risk for each item; a data and systems readiness assessment; a sequenced twelve-month roadmap; and a draft governance policy covering human review and acceptable use. Everything is delivered in working documents you own and can hand to any vendor, not a locked deck.
Do we need an AI strategy before we build anything?
Not always. If you already know the one process that's bleeding hours and it's well understood, skip the strategy work and go straight to a scoped build. Discovery earns its fee when there are competing priorities, when data quality is unknown, or when a previous pilot failed and nobody agrees on why. We'll tell you honestly which situation you're in on the first call.
Will you just recommend your own development services?
Our recommendations regularly include buying an existing product, fixing a data pipeline first, or doing nothing on a use case that doesn't pay back. That credibility is the only reason the deliverable is useful. The register we hand over is written so you can take it to any implementation partner and get comparable bids.
Keep exploring
More from the Leadify platform.
Custom AI Software
What happens after the roadmap: fixed-cost builds you own, delivered in 4 to 12 weeks.
AI Automation
The category that tops most of our roadmaps, because the hours are easiest to prove.
Will CRM be replaced by AI?
Where AI genuinely displaces software categories, and where it just makes them better.
Get a roadmap you can actually budget
Two weeks, a fixed fee credited against your build, and a ranked list of what to fund first.