AI projects don’t fail because of the AI.
They fail because of the data underneath.
Most companies have messier data than they think — the same customer listed three ways, numbers nobody can trace, documents nobody can find. Point an AI tool at that and it gives confident, wrong answers. We fix the foundation first — clean records, numbers you can trust, documents your tools can find — then the AI you’re paying for works, and keeps working. And before you spend a dollar, we’ll tell you straight whether you’re ready.
Four clear reads on your data — in about fifteen minutes.
- 25 questions, no login
- Whether you’re set up to pull it off
- How hard the move will be
- Which platform fits you
- Whether your data is ready for AI
No payment. No sales call required.
Four things, done well.
We help mid-sized companies move off old, aging data systems and onto modern ones — without the 18-month slog — and we build the clean data foundation that AI actually needs.
Move to a modern platform
We move you off your old, aging data system and onto a modern one like Snowflake or Databricks — running the old and new side by side, checking every report still matches, and keeping a way back if anything goes wrong.
Replace aging data pipelines
The behind-the-scenes plumbing that moves your data around is often held together by code from people who left years ago. We rebuild it properly — keeping what works, dropping the dead weight, and adding the tests and checks that should have been there.
Build a clean data foundation
For teams ready to start fresh on a modern cloud data platform. We set up a clean, organized, well-run foundation — and train your team to keep it running.
AI Enablement
For teams pursuing AI: we build the clean data foundation AI actually needs — one clean record per customer, numbers you can trace, documents your tools can find — and (where that foundation is solid) the AI systems on top.
It moves in stages, and every stage can be undone.
Big-bang switch-overs are where projects fail. Ours move one part of the business at a time, with the old system live until you’re ready to turn it off.
Discovery
Week 0Read what's written down. Talk to your people. Make a list of what's actually running. No proposals yet.
Assessment
Weeks 1-2Score where you stand across 5 areas. Recommend the platform that fits you, with the transparent trade-offs — not the marketing. Build the plan with clear go / no-go checkpoints.
Foundation
Weeks 3-6Set up Snowflake or Databricks. Organize the data into clean, well-run layers. Wire it up so every change is reviewed and reversible.
Switch over, one part at a time
Weeks 6-NWe move one part of the business at a time. We run the old and new side by side, check every report matches, and keep the old system live until you're ready.
Retire the old system
Final weeksThe old system goes read-only, then off. Final sign-off. Your team owns the new platform — we hand over the guides and walk away.
"They told us to wait six months. We waited six months. Then the move took eleven weeks and came in under budget."
Two checklists. One for the move, one for AI.
The same field guides we use inside paid reviews — one for moving to a modern platform like Snowflake or Databricks, and one for getting your data ready for AI. Drop your email and we'll send the PDF.
The Transparent Migration Checklist
32 questions covering the business case, your data foundation, your tools, your team's capacity, and the risks. The same pressure-test we run before quoting any move to Snowflake or Databricks.
Get the PDFThe Data Foundation for AI Checklist
22 questions covering clean records, traceable numbers, trusted definitions, well-organized documents, and keeping sensitive data protected. The one we run before quoting any AI build.
Get the PDFTwo ways to start a conversation.
Check it yourself in about fifteen minutes, or talk it through with us. Either is free.