Data + AI. Clean the data first. Then put AI on it.
Most AI projects fail because they reverse the order. We audit your data, fix what's broken, build the knowledge base, and put AI on top — where it can actually answer questions about your business.
Who it's for: SMBs whose data is messy (spreadsheets, scattered docs, half-populated CRMs), or whose AI tools return generic answers because they don't know the business.
Every other service we offer — AI Concierge, Autoshoring, Custom Apps, Hosted Private AI — works better when the data behind it is clean and indexed. If your data is the bottleneck, this is the right starting service.
What you get.
- AI that answers from YOUR data, not generic web knowledge
- Internal search that actually works — no more "I know we have a doc on that somewhere"
- Documents analyzed, summarized, classified at scale
- Decisions backed by what your business has actually written down
- Data clean enough that future AI work doesn't have to redo the foundation
What's included.
- →Data audit — what you have, where it lives, what is broken
- →Schema sanity — fix the obvious problems (duplicate fields, orphaned records, unstructured blobs)
- →Knowledge base build (RAG) — vectorize and index your docs, contracts, SOPs, emails
- →Document analysis pipeline — classify, extract, summarize at scale
- →AI Q&A layer on top — chat with your business data
- →Monthly tune — re-index new content, adjust pipelines as your work evolves
How we do it.
- 01
Audit
We map your data sources, surface quality issues, and recommend what to fix versus what to leave. Output: a written data map plus prioritized cleanup list.
- 02
Clean
Targeted cleanup — not a full data migration, just the work AI needs to be useful. Schema sanity, deduping, structuring the unstructured.
- 03
Index + deploy AI
Knowledge base, document pipelines, Q&A layer. All on your infrastructure. AI answers from your data, not from the web.
We did this for ourselves before we sold it.
Edgerton answers questions about Cyberstreams' production state by querying their data — not by reading the web. The same pattern is how every AI we deploy for clients works: cleaned data, indexed knowledge base, AI on top. The Assessment maps your data the same way.
Questions we get.
Do I need this if my data's already clean?
Maybe not. The Assessment is honest about it. Sometimes the right answer is 'your data's fine — start with AI Concierge.'
What about my CRM, accounting, EHR?
Those are data sources we connect — not systems we replace. Your existing tools stay. We just make AI able to use them.
Can we phase it?
Yes. Audit + cleanup as Phase 1, knowledge base + RAG as Phase 2, advanced pipelines as Phase 3. Most clients run Phase 1 alongside another service (Concierge / Autoshoring).
Is this just RAG with extra steps?
Mostly, plus the cleanup work to make RAG actually return useful answers. Bad RAG on dirty data is worse than no RAG.
What happens to my data?
Stays in your tenant. Lives on your infrastructure. Never trains a public model. Same data sovereignty rules as Hosted Private AI.
Related guides.
Go deeper in the Learn library.
Start with an Assessment.
Two weeks. The fee credits to any project we do together.