Knowledge Base

Turning Documents into Intelligent Knowledge Bases

Long documents slow teams down. Whether it’s a 100-page research paper, a product manual, or a policy PDF, searching for the right information is painful and inefficient.
GTWY solves this problem with RAG (Retrieval-Augmented Generation) — a system that allows AI to instantly search, understand, and summarize information from your actual documents.

With RAG, your files become smart, searchable knowledge bases that answer questions in seconds. No scrolling. No guesswork. Just accurate answers powered by your real content.

What Is Retrieval-Augmented Generation (RAG)?

RAG stands for Retrieval-Augmented Generation, a method where the AI retrieves the most relevant information before generating a response.

Traditional AI relies on what it was trained on.
RAG upgrades this with a simple formula:

RAG = Search + Think + Respond

• Search: Find relevant data from your documents

• Think: Understand context

• Respond: Generate a precise, grounded answer

This eliminates hallucinations and makes every response fact-based.

Instead of relying on memory, the AI pulls directly from your content — giving you answers you can trust.

How RAG Works

At the heart of RAG lies a process called chunking, which breaks large documents into smaller, meaningful sections called chunks.

Here’s how it works step by step:

1. Splitting the Source
   Large files or websites are divided into smaller, manageable chunks that make sense individually.

2. Searching for Context
   When a user asks a question, RAG scans through all those chunks and picks only the most relevant ones.

3. Generating the Response
   The selected chunks are passed to the AI, which reads them and generates a clear, factual, and context-aware answer.

Instead of scrolling endlessly through a document, you simply ask — and RAG finds the answer instantly.

Adding Knowledge Bases to RAG

You can build your RAG-powered knowledge base in multiple ways, depending on where your information lives:

1. File Upload

Upload documents directly — formats like .pdf, .docx, .txt, or .csv are supported.
RAG processes each file and converts it into searchable chunks for better retrieval.

2. URL to Docs

Add links to Google Sheets, Docs, or other online sources. RAG connects to those URLs and extracts usable data automatically.

3. Website Crawling

Want RAG to learn from your website? Just share the site URL — RAG crawls through the pages and builds a structured knowledge base from your content.

4. YouTube Video Crawling

This one’s unique — RAG can even process YouTube videos by extracting spoken or captioned content and turning it into searchable knowledge.
Your video tutorials, webinars, or product demos can now power intelligent responses too.

This flexibility means your knowledge base can come from anywhere — documents, websites, or videos — all unified under one system.

Smart Chunking: How RAG Understands Content

RAG’s real strength lies in how it processes your information. It doesn’t just split files randomly — it uses intelligent chunking methods to preserve meaning and structure.

1. Recursive Chunking

Breaks documents into equal, digestible sections — ensuring every piece is readable and consistent in size.

2. Semantic Chunking

Groups related ideas together by meaning. This way, chunks contain full, contextually complete thoughts instead of random text fragments.

3. AI-Based Chunking

Uses advanced AI logic to identify natural breakpoints in your content — dynamically adjusting chunk sizes based on structure and importance.

Each method ensures your knowledge base remains coherent, searchable, and optimized for accuracy.

Why RAG Matters

RAG is more than just a document reader — it’s a context engine.
By combining retrieval and generation, it ensures your AI always responds with real, grounded, and up-to-date information.

Perfect for:

• Customer Support: AI can instantly answer queries from product manuals or FAQs.

• Internal Knowledge Systems: Employees can search policy or training documents quickly.

• Research Teams: Extract findings from reports and papers in seconds.

• Product Teams: Power in-app knowledge bases or chatbots with real content.

Final Thoughts

GTWY’s RAG feature transforms static information into dynamic, searchable intelligence.
Ask any question — and your AI retrieves the exact content you need, reads it, and gives you a precise, grounded answer.

Whether you're building support tools, internal search, research assistants, or smart in-app chat, RAG removes the friction of document reading and replaces it with instant, accurate retrieval.

Stop scrolling. Start asking.
Let RAG do the heavy lifting.