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RAG & Knowledge AI: Answers from your data, not the internet

Build AI that answers questions using your internal documents, policies, and knowledge bases - accurate, sourced, and up to date.

Key Features

Knowledge Connection

Connect AI to your internal documents, policies, and knowledge bases

Source Citations

Grounded answers traceable to the original document

Real-Time Updates

Keeps up as your documents change, no retraining needed

Access Control

Users only see answers from documents they're authorized to access

Technologies We Use

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What is RAG & Knowledge AI?

Retrieval-Augmented Generation connects an LLM to your internal data - documents, policies, SOPs, knowledge bases. Instead of generating answers from training data, the AI retrieves relevant information from your sources and generates grounded, accurate responses with citations. It knows what it knows, and tells you when it doesn't.

Benefits

Make your AI feel native to your business: faster, more accurate, and a true competitive advantage from day one.

Employees find answers in seconds instead of searching across systems

Consistent, accurate responses based on your approved documents

Institutional knowledge preserved and accessible even as teams change

Why It Matters

Your organization's most valuable knowledge is locked in documents, wikis, and SharePoint folders that nobody reads. RAG makes that knowledge instantly accessible - employees ask questions in plain language and get accurate answers backed by your actual documents, not AI guesses. No more searching five systems to find one answer.

What You Get

An AI assistant that answers questions from your internal documents with source citations
Automatic sync - the knowledge base stays current as documents are added or updated
Role-based access so users only see answers from documents they're authorized to access
Measurable accuracy metrics so you know how well the system is performing

How We Deliver

We start by auditing your document landscape - what you have, where it lives, who needs access. Then we ingest your documents, build the vector index, and configure the retrieval pipeline for accuracy and speed. We test against real questions your team asks and refine until the answers are consistently accurate. Production deployment includes monitoring, feedback loops, and automatic document sync so the system stays current.

Our Process

1

Assess

1–2 weeks

Audit your document landscape, identify high-value knowledge sources, define access rules.

2

Build

4–6 weeks

Ingest documents, build vector index, configure retrieval pipeline, test accuracy.

3

Deploy

2–3 weeks

Launch with monitoring, feedback loops, and automatic document sync.

Use Cases

Health Insurance

Policy Q&A for Members

Members and agents get instant, accurate answers about coverage, benefits, and claims procedures.

Healthcare

Clinical Protocol Lookup

Clinicians query treatment protocols, drug interactions, and care guidelines in natural language.

Financial Services

Compliance Reference

Compliance teams instantly find relevant regulations and internal policies during audits.

Frequently Asked Questions

Common questions about RAG & Knowledge AI.

PDFs, Word, HTML, Confluence, SharePoint, Google Docs, and most structured/unstructured formats.

Automatic re-ingestion pipelines keep the knowledge base current as documents change.

The system tells the user it doesn't have enough information rather than guessing - no hallucinated answers.

Yes. Everything runs in your private environment. Documents never leave your infrastructure.

NEXT STEP

See how RAG works with your data

Private AI that works with your existing systems and delivers transparent, compliant automation. Tell us where you're stuck - we'll show you what's possible.

Accelyst AI

Knowledge Base

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