Approach
Stop starting over.
Most AI pilots stall because each one is a one-off. We run every project through the same four steps, so each one makes the next one easier.
The flywheel
- 1
Connect
We bring your data sources together: accounting, operations, the spreadsheets that matter and the documents around them. Nothing is thrown away, and nobody has to change tools on day one.
- 2
Model once
We sit with the people who know the business and write down what each number and term means, in one place. This is where your team’s knowledge becomes something every tool can use.
- 3
Serve everywhere
Reports, spreadsheets, internal apps and AI assistants all draw on those same definitions, so the answer is the same wherever someone asks.
- 4
Reinvest
We document what each project taught us and fold it back in. The next project starts further ahead than the last one did.
What your company knows is its greatest asset.
The discipline is proven. What's possible is new.
Knowledge management is an established practice: work out what an organization knows, write it down in a form others can use, and keep it current. For most companies it has always cost more than it returned.
Generative AI changes the sums. Documentation, organization and retrieval that once took a dedicated team can now be kept up as part of everyday work. Tuck Labs pairs that capability with the practice that tells you what is worth capturing in the first place.
It also means your team's expertise is the foundation of the work, not the thing being automated.
How we work
Start with the decision, not the data.
We begin with the business problems where better information would change what you do, and work backwards to what needs building.
Agree what success is worth before writing code.
Hours saved or dollars gained, named up front, so everyone can tell whether the work paid off.
Give every pilot a stopping point.
If a prototype is not being used by an agreed date, we stop and spend the budget somewhere better.
Buy before you build.
If a standard product does the job, we will say so. Custom software has to earn its long-term upkeep.
Every answer traces to its source.
A number from an AI tool should lead back to the record it came from, so people can check it and trust it.
Build for the people who will use it.
Adoption is designed in from the start: we learn how your team works today and bring them along, so the new way is easier than the old one.