Agentic RAG Architecture
Autonomous decision-making with intelligent orchestration across retrieval, augmentation, and generation layers
Augmentation
Autonomous context orchestration with intelligent routing (fast-path vs deep extraction), conversation memory resolution, and adaptive strategy selection based on query complexity
Retrieval
Intelligent multi-stage funnel (100→50→20→3) with adaptive search strategies, semantic vector matching, LLM-powered gift appropriateness scoring, and diversity-aware selection
Generation
Context-aware streaming generation with parallel warmup, dynamic product injection during narration, smart category suggestions, and conversation state persistence for seamless multi-turn intelligence
Key Features
Built for performance, intelligence, and user experience
Parallel Execution
Non-blocking architecture with immediate skeleton response. Dramatically faster time to first content with parallel processing.
Context Preservation
Intelligent followup handling with “show more” support, smart exclusion, and conversation memory
Semantic Search
Multi-stage funnel with vector search, LLM reranking, diversity selection, and gender affinity boost
Multi-Language
Native support for Estonian and English with language-aware search and cultural relevance scoring
Author Resolution
Multi-stage author detection, pronoun resolution with LLM fallback, and disambiguation handling
Graceful Fallback
Pool exhaustion detection, automatic retry strategies, and transparent acknowledgments to users
Technology Stack
Powered by cutting-edge AI and web technologies
Frontend
- Next.js 14+ with TypeScript
- Motion.dev for animations
- Real-time streaming UI
Backend
- Vercel AI SDK
- Convex real-time database
- Vector embeddings
AI Models
- LLaMA 8B (context extraction)
- GPT-5.1 (generation)
- Cohere Rerank v3.5