Advanced RAG Architecture
Our hybrid retrieval system combines the best of keyword and semantic search to deliver precise, context-aware responses.
Enhanced Contextual Retrieval
Kritova's unique hybrid approach ensures both keyword relevance and deep semantic understanding of queries.
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Combines BM25 (sparse) & Dense Embeddings (semantic)
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Semantic text splitting preserves context
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Configurable chunk size and overlap
Simplified RAG Flow
Technical Implementation
Advanced systems that power Kritova's intelligence and adaptability
Memory & Caching
Efficiently stores and retrieves information for context and performance optimization.
Adaptability Systems
Learns and adjusts based on user interaction patterns and feedback mechanisms.
Evaluation & Quality
Ensures response accuracy, relevance, and faithfulness to source material.
Advanced Processing
Sophisticated techniques to enhance queries and refine responses.
Operational Architecture
Scalable and reliable infrastructure to handle millions of requests.
User Experience
Designed for natural, intuitive interactions with human-like qualities.
Development Roadmap
Our journey of continuous improvement and innovation
Initial RAG Implementation
Launched with basic hybrid retrieval (BM25 + Dense) and Gemini Pro generation.
Advanced Optimization
Added cross-encoder reranking, HyDE query transformation, and response refinement.
Gemini Flash 2.0 Integration
Upgraded to Gemini Flash 2.0 for faster, more cost-effective generation.
Evaluation Framework
Implemented RAGAS metrics and continuous evaluation pipeline.
Personalization Engine
Added adaptive retrieval parameters and user preference learning.
Performance Metrics
Kritova delivers exceptional performance across all key indicators, ensuring fast, accurate, and reliable assistance.
Retrieval Effectiveness
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