From messy Drive folder to AI-ready data.
Every brand has the folder: brand guides as PDFs, spreadsheets with headers on row 3, multi-tab workbooks only one person understands. The Data Architect reads every file, decides what should become searchable knowledge and what should become queryable tables, and shows you the plan before a single byte is imported. You approve. It ships the data. Mother gets to work.
Access is invite-only while we onboard early brands.
Someone has to open every file.
Before your AI can use your data, a human has to look at each document, decide what it is, reshape it into something importable, and load it. Delete the two junk rows above the header. Pick the right tab out of six. Figure out whether that "report" is actually a table. Split the prose from the numbers. That someone has been your team — or nobody, which is why the folder is still sitting there.
The Data Architect is that someone.
Scan. Plan. Apply.
Share your files
Share a Google Drive folder link. That's the whole integration — no OAuth screens, no exporting to CSV, no reformatting homework for your team.
Review the plan
The Architect inspects every file and returns a one-page import plan: this PDF becomes brand knowledge your AI can cite. This spreadsheet becomes a table — headers found on row 3, junk rows dropped. This column gets semantic search. Anything ambiguous is flagged for a human with a specific reason — never guessed at silently.
Approve — and it's live
One approval and every file is converted and imported: clean tables you can query in plain English, documents your AI can search and cite. You get a full receipt — what landed, what was skipped, and why.
Built for files as they actually are.
Headers on row 3
Junk rows above the real table are detected and dropped. Columns get proper names and types.
Multi-tab workbooks
Each tab is assessed on its own. The sales data becomes a table; the scratch tab gets skipped — with a reason.
Docs and PDFs
Brand guides, research, meeting notes — extracted, indexed, and searchable. Your AI cites them by source.
Text inside tables
Review dumps and feedback columns get semantic search, so "what do customers say about sizing?" just works.
Report-shaped sheets
A formatted report isn't a table. Instead of force-importing garbage, the Architect flags it with a specific fix.
Safe re-runs
Updated a file? Re-run the folder. Changed files refresh their tables in place — no duplicates, ever.
Your data. Your approval. Every time.
Nothing imports without sign-off
The review plan isn't a suggestion — it's a gate. Imports only run on files you've approved, enforced on our servers, not by AI good manners.
Every file gets an answer
Imported, skipped, or flagged — each file ends with an explicit outcome and a reason. No silent failures, no mystery gaps in your data.
Honest about uncertainty
When a file is genuinely ambiguous, the Architect says so and tells you what it needs — it doesn't guess and hope.
Questions
What file types does it handle?
Google Docs, Google Sheets, Excel workbooks, PDFs, CSVs, and plain text or markdown files in your Drive.
Does it change anything in our Drive?
No. Your Drive is read-only to us. Converted copies live in your Gentic workspace with a full audit trail.
What happens to files it can't figure out?
They're flagged for review with a specific reason and a suggested fix — visible in the plan before anything runs.
How is it priced?
Per file converted — you only pay for what actually lands. We'll walk through pricing on the call.
Stop being your AI's data-entry team.
Book a call and bring your messiest folder. We'll walk through what the Architect would do with it — file by file.