Advanced RAG Technology

Our proprietary Retrieval-Augmented Generation system delivers unmatched accuracy, context-awareness, and transparency for enterprise knowledge.

IntraGPT RAG Architecture

Our proprietary Retrieval-Augmented Generation pipeline delivers accurate, contextual responses

Document Processing
Knowledge Embedding
Query Understanding
Context Retrieval
Answer Generation

Document Processing

Our advanced document processing pipeline handles PDF, DOCX, TXT, CSV, and more. Documents are parsed, cleaned, and chunked into optimal sizes for retrieval.

PDF
DOC
TXT
CSV
Document Chunking
Chunk 1: Lorem ipsum dolor sit amet, consectetur adipiscing elit...
Chunk 2: Lorem ipsum dolor sit amet, consectetur adipiscing elit...
Chunk 3: Lorem ipsum dolor sit amet, consectetur adipiscing elit...

Key Advantages of Our RAG Technology

What makes IntraGPT's implementation stand out from the competition

Superior Accuracy

Responses grounded in your specific documents, reducing hallucinations and inaccuracies common in traditional AI systems.

Contextual Understanding

Multi-document reasoning that connects information across your entire knowledge base.

Ultra-Fast Retrieval

Our proprietary vector database enables sub-second retrieval even across millions of documents.

Source Citations

Every response includes references to source documents, ensuring transparency and accountability.

Adaptive Learning

System improves over time by learning from user interactions and feedback.

Enterprise Ready

Built for scale with enterprise-grade security, compliance, and integration capabilities.

Technical Excellence

Our RAG implementation goes beyond standard approaches by incorporating proprietary advancements in document processing, retrieval, and response generation.

Multi-stage Document Processing

Advanced chunking algorithms that preserve semantic coherence while optimizing for retrieval. Our system handles tables, charts, and structured data with specialized extractors.

Hybrid Retrieval System

Combines dense vector retrieval, sparse retrieval (BM25), and knowledge graph navigation for comprehensive information gathering across your documents.

Context-Aware Response Generation

Proprietary prompt engineering and model fine-tuning ensure responses are factually grounded, coherent, and directly relevant to user queries.

Performance Benchmarks

Response Accuracy96%

Based on factual correctness compared to source documents

Retrieval Speed98%

Average retrieval time of <100ms for most queries

Hallucination Reduction92%

Reduction in factual errors compared to standard LLMs

Context Utilization95%

Effective use of retrieved context in generated responses

Benchmarked Against Competitors

Our system outperforms leading RAG solutions across all key metrics in independent evaluations.

Enterprise-Grade Implementation

Designed for seamless integration with your existing systems and workflows

Secure Private Cloud

Dedicated deployment in your own cloud environment or on-premises infrastructure.

Custom Integrations

Connect with your existing knowledge management systems, CRMs, and enterprise software.

Detailed Analytics

Comprehensive usage metrics, query patterns, and performance analytics.

Custom Data Connectors

Specialized connectors for enterprise systems like SharePoint, Confluence, and Salesforce.

Supported Integrations

Microsoft SharePoint
Confluence
Salesforce
Google Workspace
ServiceNow
Jira
OneDrive
Custom REST APIs

Experience the RAG Difference

See how our advanced RAG implementation can transform your organization's knowledge management and customer support.