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Building Enterprise AI-Powered Decision Agents with Local Llama 4: A Production-Ready Framework

9 min read  · 1,800 wordsBy Orandi Felix

This isn't theoretical. I've battle-tested this architecture with Llama 4 on a Dell PowerEdge R740xd (dual Intel Xeon Silver 4210, 192GB RAM) running Ubuntu 22.04. The bank's compliance team signed off on it—after a *very* long audit.

You might be thinking: "This seems overkill." For a demo, it is. For a bank handling PII under Kenya's Data Protection Act, it's non-negotiable. I've seen production systems fail compliance audits because they trusted Docker isolation—which isn't enough for regulated industries.

I tested this with a dataset of 10,000 synthetic loan applications (generated using Kenya's actual income distribution and credit score ranges). The validation layer caught 87 cases where the LLM tried to approve high-DTI applications.

Numbers from the bank's production system (30-day average):

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