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Overview
Engineering practice of Chris Cowart — systems architecture, agentic AI, and infrastructure automation. Built from the Colorado Rockies.
News
The Same Entity Problem: Why every payments, fraud, and compliance company is solving the same thing
Businesses are shape-shifters - they merge, rebrand, relocate, change banks. The universal problem underneath fraud, compliance, payments, and supply chain isn't string matching. It's tracking entities through time.
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The Verification Layer Is the Product
I ran my production KYB pipeline at FP16, INT8, and INT4. Accuracy held at 92% across all three. A LoRA fine-tune dropped it to 12%. The model wasn't the variable.
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The Three Enterprise Layers Are Collapsing Into One
For twenty years, enterprise software separated CRM, orchestration, and back-office into three layers with three vendor contracts. A confidence-gated decisioning layer is collapsing all three - and the vendors know it.
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Quantization, LoRA, and the 8% Problem: Benchmarking Local LLMs for Production AI
I benchmarked 7 model variants across 3 quantization levels, tested a 3B challenger, built a self-training pipeline, and attempted QLoRA fine-tuning. The fine-tuning failed catastrophically. Here's what I learned.
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I Ran My KYB Engine at Three Quantization Levels. Accuracy Didn't Move. Cost Dropped 6x.
I benchmarked FP16 vs INT8 vs INT4 quantization on a real KYB verification pipeline. Zero accuracy loss. 5.6x faster. 6x cheaper. Here's the data.
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