Knowledge Base (RAG)

Ingesting documents, configuring chunking strategies, and managing vector retrieval.

The Knowledge Base is your agent's long-term memory. It allows the AI to "read" your proprietary documents (PDFs, Manuals, Policies) and answer questions based only on that data.

Iqra AI uses a RAG (Retrieval Augmented Generation) pipeline. We do not retrain the model; we inject relevant information into the context window in real-time.

The Ingestion Pipeline

It is important to understand how we treat your data. We do not store your raw files. Once uploaded, a document is converted into text, chunked, and embedded.

1. Creating a Group

Documents are organized into Groups (e.g., "HR Policies", "Technical Manuals"). Retrieval settings are defined at the Group level.

General Chunking

Splits text linearly based on character count.

Best for: Simple text files, FAQs.
Settings: Max Chunk Length (e.g., 500 chars), Overlap.

Parent-Child Chunking

High Precision. Splits documents into small "Child" chunks for precise searching, but retrieves the larger "Parent" chunk for context.

Best for: Complex documents where a single sentence loses meaning without its surrounding paragraph.

Retrieval Configuration

Vector Search: Matches semantic meaning (concepts).
Full Text: Matches exact keywords.
Hybrid Search (Recommended): Combines both scores for best results.
Reranking: Re-orders the top results using a high-precision model to ensure the most relevant chunk is first.

2. Managing Documents

Once a group is created, you can upload and manage the data.

Upload & Pre-processing

Upload PDF, DOCX, TXT, or MD files. You can enable Cleaning Rules to automatically strip URLs, emails, or excessive whitespace during extraction.

Chunk Management (Crucial)

After processing, the file exists only as a List of Text Chunks.

Edit Chunks: If the PDF parser messed up a table, you can click on the chunk and fix the text manually.
Add Chunks: You can manually add a text block (e.g., a quick policy update) without uploading a file.
Delete Chunks: Remove irrelevant footers or legal disclaimers that confuse the AI.

3. Connecting to Agent

Creating a database is useless if the Agent can't access it.

You must link your Knowledge Base Group to an Agent in the Agent Studio.

Search Triggers

Simply linking the KB doesn't mean the agent searches it every time. You must define a Search Strategy (e.g., Always Search, Smart Classifier, or Script Tool).

Read the Agent Intelligence Guide to configure when the agent searches.

Roadmap: Future Capabilities

We are actively expanding our Knowledge Engine.

Dynamic Data Sources

Live Sync. Instead of manual uploads, connect to Google Drive, Notion, or a Website URL. The system will periodically re-crawl and re-index the data to keep the agent up to date automatically.

GraphRAG

Knowledge Graph. Moving beyond simple vectors. We plan to map relationships between entities (e.g., "Product A is compatible with Product B"). This allows the agent to answer complex reasoning questions that standard RAG fails at.