Intelligent RAG-based Corporate Knowledge Management System
Semantic search, document processing, and multimedia transcription via conversational interface.
Solution Overview
A platform for managing corporate knowledge base with automatic document and multimedia processing. The system handles segmentation, indexing, and content organization - from PDFs and presentations to video recordings. Access through a conversational interface (e.g., messenger).
Market Positioning
Up to 80% of corporate information is stored in unstructured form - documentation, video materials, correspondence. Traditional full-text search requires exact term matching: if the document says "delivery" but the query says "shipping" - nothing is found. This reduces information retrieval completeness.
Development Goals
- Automate indexing of documents in various formats
- Process multimedia content with text extraction
- Enable semantic search across the corporate knowledge base
- Provide an intuitive interface for end users
Knowledge Base Management
The system provides an administrative interface for the full content lifecycle:
Content Addition - single upload or batch file import.
Document Processing - automatic segmentation and indexing.
Video Transcription - extraction and indexing of speech content.
Collection Management - creation, clearing, backup.
Cloud Storage Integration
For uploading large volumes of data, integration with a cloud storage system is implemented. Users receive a temporary link to upload files that are automatically processed by the system.
Document Processing
A pipeline with adaptive segmentation strategy selection depending on content type:
Text Files - semantic segmentation with boundary detection based on semantic coherence.
PDF, DOCX, PPTX - hybrid segmentation preserving document structure and tables.
Images - optical character recognition (OCR) for text extraction.
Video and Audio - transcription with timestamp-based segmentation.
Semantic Segmentation
Based on analyzing cosine distance between embeddings of adjacent sentences. Segment boundaries are set at points of sharp semantic coherence change - this ensures the formation of thematically coherent fragments.
Multimedia Transcription
A speech recognition service is integrated for processing audiovisual content. The result includes timestamps for navigation to specific moments in the video.
- Asynchronous processing of long recordings
- Automatic audio track extraction
- Multilingual content support
- Segment timestamp preservation
Technical Architecture
Microservices architecture ensuring scalability and fault tolerance. Four main layers:
How RAG Works
RAG (Retrieval Augmented Generation) combines information retrieval and generative models. The system dynamically enriches context with relevant documents from the knowledge base - working with current information without model retraining.
Vector Representations
The BGE-M3 model converts text into 1024-dimensional vectors. Semantically similar texts are located close to each other in vector space - search is based on meaning, not exact word matching.
Dense Vectors - deep semantics of the query.
Sparse Vectors - exact lexical matches.
Hybrid Search - combination of both approaches for better results.
Search Algorithm
- Parallel Search - simultaneous dense and sparse search across all collections
- RRF Fusion - merging results considering positions: RRF_score(d) = Σ 1/(k + rank_i(d))
- Reranking - evaluating query-document pair relevance
- Threshold Filtering - filtering out results below threshold
Multimodal Search
Unified search covers all content types:
- Text Documents - FAQs, instructions, articles
- Structured Data - product catalogs
- Video Content - by transcription with timestamps
- Web Pages - indexed site materials
Results
The hybrid approach with reranking outperforms basic methods:
Scalability
- Linear scaling with knowledge base growth
- Support for multiple collections
- Parallel query processing
- Incremental index updates
Practical Applications
Support Service - instant access to relevant information for operators.
Internal Documentation - search across corporate knowledge base.
Staff Training - navigation through training video materials.
Product Catalog - semantic search by characteristics.
Key Advantages
- Automatic Processing - documents, video, audio are indexed without manual work
- Batch Import - cloud storage integration for uploading large volumes
- Collection Management - creation, clearing, backup
- Multimedia Transcription - video and audio converted to text with timestamps
- Semantic Segmentation - splitting by meaning, not by characters
- Multimodality - unified search across all content types
- Hybrid Search - ~91% accuracy through multi-stage ranking