Document Verifier SLM (Deep Learning / Transformer Architecture)
Built a production-style identity document verification system using a custom Dual-Encoder Cross-Attention Transformer trained from scratch in PyTorch on 500K synthetic samples.
Designed a character-aware tokenizer and transformer architecture achieving 93% test accuracy for Aadhaar/document forgery detection. Implemented curriculum learning, EMA, focal loss, and hard negative mining; developed a three-tier inference pipeline with explainable field-level attribution.
PyTorch HuggingFace
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Neural Archive v3.0 (RAG & LLM Infrastructure)
Engineered an end-to-end RAG platform using FastAPI, ChromaDB, Gemini embeddings, and IBM Docling for OCR-aware ingestion of technical documents. Implemented semantic chunking, vector persistence, neighboring-context retrieval, and 3D embedding visualization via PCA + Plotly.
FastAPI ChromaDB Gemini API
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