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RAG

Enterprise RAG over SharePoint, file servers, SQL databases, and websites, AI that knows your context.

Generic ChatGPT answers general questions. Our RAG (Retrieval-Augmented Generation) platform answers questions about YOUR documents, YOUR processes, YOUR data. Connect SharePoint, OneDrive, Google Drive, your SQL databases, and your websites, AI becomes the internal expert of your business.

Overview

AI that knows your business inside out

Why are your employees still manually searching SharePoint to find a vendor contract, the latest version of a procedure, or a contact's phone number? Our RAG center indexes your authorized data sources (with strict respect for existing permissions) and instantly answers natural-language questions, with citations to source documents. It's ChatGPT, but for your business's internal intelligence.

What we deliver

01

SharePoint and OneDrive connectors

Automatic indexing with respect for Microsoft 365 permissions, each user only sees what they already have permission to see.

02

Google Drive and Workspace connectors

Read Drive, Docs, Sheets, Calendar with Google authentication, native permissions respected.

03

SQL agents for databases

Ask natural-language questions about your CRM, ERP, product database, AI translates to SQL queries and synthesizes the answer.

04

Website indexing

Corporate site, knowledge base, public documentation, unified search across all your sources.

05

PDF editing and diagram creation

PDF editing via natural-language instructions, Mermaid/Draw.io diagram generation from descriptions, OCR for scanned PDFs.

06

Intelligent documentation center

AI-powered internal wiki: auto-suggestion of related pages, summary generation, identification of stale pages.

Our approach

How we deploy enterprise RAG

1

Source inventory

Mapping of your relevant data sources: SharePoint, files, databases, wikis. Identification of permissions to respect.

2

Initial indexing

Content extraction, vector embedding generation, storage in a Canadian database. Precision tests on typical questions.

3

User interface integration

Deployment in Teams, Slack, or standalone web interface. SSO authentication, access control by department.

4

Continuous updates

Automatic incremental synchronization. Response quality monitoring. Adjustments based on user feedback.

Why Hilo Tech

Why our RAG works where others fail

  • Source permissions strictly respected, an employee sees in AI what they already see in SharePoint, no more.
  • Explicit citations for every answer, the user can click on the source to validate.
  • Incremental indexing, a modified document is updated in minutes, not days.
  • Canadian hosting of vector indices, your indexed data never leaves the jurisdiction.
  • Rigorous quality evaluation, we measure precision before production, not after.

Frequently asked questions

Will the AI see confidential documents it shouldn't?
No. We respect the native permissions of your stack (SharePoint, Drive, etc.). If an employee doesn't have access to a document in SharePoint, AI will never present that content to them. Permissions are checked on every request, not just at indexing.
How long does it take to index a typical SharePoint?
For ~50,000 documents: 24-48 hours for initial indexing, then minutes for incremental updates. You can use the platform as soon as a subset is indexed.
How do you verify AI gives correct answers?
Every answer includes citations to source documents, the user can validate in one click. We also measure precision via known test questions (before production) and a user feedback system (in production).
Which SQL databases are supported?
PostgreSQL, MySQL, SQL Server, Oracle, BigQuery, Snowflake, Redshift. SQL agents work read-only by default to prevent accidental modification.
How much does enterprise RAG cost?
Variable based on document volume indexed and number of users. For ~50,000 documents and 25 users: roughly $800 to $1,500/month in infrastructure and AI, plus initial setup cost. Much cheaper than enterprise solutions like Glean or Microsoft Copilot Enterprise.

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