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AI & Automation6 min read

Devesh JoshiCo-founder, product

Nine years building AI platforms serving 12,000+ engineers. LLM platforms, agentic systems (MCP), and multi-model safety evaluation.

On-premise SLMs: Running Llama 3.3 and DeepSeek distill models for HIPAA & GDPR privacy

How enterprise teams deploy lightweight, quantized Small Language Models on isolated Cloud infrastructure for sub-20ms latency and strict data compliance.

Why data privacy demands on-premise SLMs

Sending sensitive medical records or financial transactions to third-party public LLM endpoints introduces compliance vulnerabilities under HIPAA and GDPR.

Modern 8B and 14B parameter quantized SLMs (Llama 3.3, DeepSeek-R1 Distill) deliver near-GPT-4 accuracy on domain-specific extraction tasks while running entirely on private cloud GPUs.

Topic Focus & Target Concepts

local SLM deploymentLlama 3.3 enterprise privacyDeepSeek distill on premiseHIPAA compliant AI architectureedge AI model quantization

This is the work behind our AI and automation practice — agents with real grounding, voice intake, and retrieval that answers from your records rather than the model's training data.

Agents with real tool access

Running into this in your own stack? Twenty minutes, no deck.

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