Case Study — Multi-Agent AI Systems
A multi-agent GraphRAG system that autonomously writes reliable, bias-aware Wikipedia-style articles with verifiable provenance on every claim.

Generated knowledge bases hallucinate. Building an article-generation system that could be trusted meant solving source verification, bias detection, and provenance tracking at once.
Claims verified against sources
~94% traced to origin
Articles generated per run
20+ with full citations
Hallucination rate
Reduced >50% vs. baseline RAG

Batch Disclosure — Price-Moving Catalyst Detection
An AI-powered system that scans ASX and SEC filings for forward-looking disclosures — contracts, M&A, guidance — that move micro-cap prices before the market catches on.

Llama2 QLoRA Healthcare — Medical LLM on One GPU
A fine-tuned LLaMA-2-7B medical assistant trained with QLoRA on a single GPU — production-quality LLM fine-tuning without an expensive compute cluster.
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