Geopolymer Research Library – AI-Powered Scientific Research & Knowledge Discovery Platform
The Problem
Scientific knowledge was scattered across patents, journals, theses, conference papers, and technical reports, making research slow and inefficient. Traditional keyword search often failed to discover semantically relevant content, while generic AI tools lacked reliable source attribution. Researchers needed a way to quickly access trustworthy, domain-specific knowledge while maintaining traceability to original scientific sources.
How We Solved It
Built a domain-specific RAG platform that transforms a curated scientific document library into an AI-powered research assistant called Sherlock. The system converts documents into vector embeddings, performs semantic retrieval using Pinecone, and generates grounded responses through Anthropic Claude. Researchers can filter content by publication type, receive source-backed answers, personalize AI explanations based on expertise, save research sessions and notes, and export findings. A complete document-ingestion pipeline automates PDF processing, metadata extraction, embedding generation, indexing, and library expansion.
Deliverables
- Sherlock AI Research Assistant
- Retrieval-Augmented Generation (RAG) Engine
- Scientific Semantic Search System
- OpenAI Embedding Pipeline
- Pinecone Vector Search Infrastructure
- Research Notes & Knowledge Workspace
- Source Attribution & Citation System
- Real-Time WebSocket Progress Updates
- Administrative Portal
- Analytics Dashboard
- Subscription Management Module
Results & Impact
- Enabled semantic search across patents, journals, theses, technical reports, and conference papers.
- Delivered grounded AI responses with source attribution and relevance scoring.
- Automated PDF ingestion, chunking, embedding generation, and indexing.
- Reduced time spent manually reviewing scientific literature. Improved research accuracy through source-backed AI responses.
- Increased trust in AI-generated outputs through transparent citations and supporting documents.
Assets
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