33KB

OmniInfer

33KB. 7B parameter inference. Data never leaves. Because it can't — there's no network code.

Healthcare Legal Fintech

The Problem

Organizations need LLM capabilities but cannot send sensitive data to cloud APIs. Healthcare records through OpenAI violate HIPAA. Legal documents through Azure AI risk breach. The alternative — running PyTorch locally — requires 2GB+ of runtime with hundreds of pip dependencies, each a potential vulnerability.

The Solution

OmniInfer runs 7B parameter LLM inference in a 33KB binary that does not contain networking code. Data exfiltration is not a policy decision — it is a physical impossibility. The binary does not know how to open a socket because the code for sockets does not exist in the 33KB.

Why Bare-Metal Matters

The security guarantee is architectural, not configurational. There is no firewall rule to misconfigure, no environment variable to leak, no dependency that phones home. The binary physically cannot transmit data because it was compiled without network syscalls. This is provable by static analysis of the 33KB binary.

Technical Specifications

Feature Value
Binary Size 33KB
Model Support 7B parameter LLMs (GGUF Q4_K/Q6_K)
Networking None — physically cannot exfiltrate
Dependencies None
Runtime None (no Python, no PyTorch)
Compute CPU-only (SSE2/AVX2)
Architecture 28-layer transformer inference

Comparison

OmniInfer OpenAI API Python + PyTorch
Size 33KB Cloud service2GB+ runtime
Data leaves server Impossible (no network code) Always (API calls)Possible (pip packages)
Dependencies None Internet + API keyPython + CUDA + PyTorch + ...
HIPAA compliant Inherent BAA requiredDepends on deployment
Offline operation Yes (only mode) NoYes
Supply chain CVEs 0 N/A (cloud)Hundreds (pip)

Use Cases

Healthcare AI (HIPAA)

Process patient records with LLM intelligence on local servers. HIPAA compliance is inherent — the binary cannot send data anywhere because it has no networking capability.

Legal Document Analysis

Analyze contracts and legal documents without data leaving the firm. Attorney-client privilege is maintained by architecture, not policy.

Financial Risk Analysis

Run AI analysis on financial data without exposing it to third-party APIs. Regulatory compliance is built into the binary.