AI-Ready Data
Grounded data for your AI agents, from the spreadsheets your teams actually use.
Trusted by companies large and small
How it works
How Sheetgo makes your spreadsheet data AI-ready
Four stages, one clean pipeline — from raw files to agent-ready context.
Normalize
Clean inconsistent headers, collapse duplicate files, and lock in a schema your AI can actually follow.
Govern
Permissions, audit logs, and lineage — so every row has a known origin before it reaches a model.
Ground
Land prepared datasets in BigQuery for RAG, vector stores, or direct agent access, with no glue code.
Serve
Native Gemini Enterprise and MCP interfaces — your agents query spreadsheet data through the same protocol they query everything else.
Solution
Stop your AI from hallucinating on your spreadsheets
Clean source layer
Works where your data already lives
OneDrive, SharePoint, Dropbox, Google Workspace — the permissions your security team approved stay intact.
BigQuery grounding
Pipe prepared datasets straight into BigQuery for RAG, vector indexing, or direct agent context.
Gemini & MCP native
Expose spreadsheet data to Gemini Enterprise and MCP-compatible agents without building custom integrations.
Every change versioned
Schema evolution and transformation logs — so when your AI says something, you can prove where it came from.
Security
Industry-leading compliance
Trusted by over 6 million users in companies of all sizes, Sheetgo complies with SOC 2 Type II, GDPR, and CASA Tier 3. It is a top Google Workspace Recommended solution and is available on the Google Cloud Marketplace for easy procurement compliance.
Frequently Asked Question
Dive deeper into AI-Ready Data
How grounding works, which agents we support, and what security looks like.
What does AI-ready actually mean?
Your spreadsheet data has been normalized, governed, and made schema-stable so AI agents (Gemini, MCP, or custom) can retrieve it without hallucinating on duplicate files or stale formulas. Your agents see one trusted dataset — not Q3_Final_v4.xlsx.
Which AI agents and protocols are supported?
Sheetgo’s AI-Ready layer exposes data to Gemini Enterprise, MCP-compatible agents, and any system that can query BigQuery or an open API. ADK integration is on the near-term roadmap.
How is this different from just connecting my spreadsheets to an LLM directly?
A raw connection hands the LLM a dozen messy files — it hallucinates because it can’t tell which is authoritative. Sheetgo is the clean layer in between: normalized schemas, enforced permissions, versioned changes, and BigQuery-ready output.
Do I need BigQuery to use AI-Ready data?
No. BigQuery is the preferred landing zone for RAG and agent context, but Sheetgo can also serve prepared datasets via API or direct Google Sheets / Excel access.
How is data security handled in the AI-Ready layer?
The same compliance posture as the rest of Sheetgo: SOC 2 Type II, GDPR, CASA Tier 3. Source-system permissions (SharePoint, Drive, OneDrive) are preserved, and every transformation is logged for audit.
What about schema changes? My spreadsheets change every month.
Schema evolution is tracked — when columns are added, renamed, or removed, Sheetgo versions the change so AI outputs stay traceable to a known state.
Is AI-Ready Data a separate product, or part of Enterprise?
It’s part of Sheetgo Enterprise — a capability of the Enterprise tier, not a standalone product.
How long does a typical AI-Ready rollout take?
A pilot with a single department’s data can be up and running in under two weeks. Larger multi-department deployments take longer depending on governance review. Book a demo to scope your rollout.
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