Zero-Cloud Air-Gapped Desktop Intelligence
For defense, financial services, healthcare, and IP-sensitive enterprises, cloud LLM APIs present compliance risks. Our local AI agents run completely offline on workstation hardware (NVIDIA GPUs / Apple Silicon) using Ollama and local SQLite vector indices.
Production-tested execution flow designed for multi-region reliability and security.
Monitors local file folders or user desktop keyboard/mouse triggers.
Extracts local text using ONNX embedders with zero network calls.
Executes GGUF/INT4 quantized Llama 3.3 via Ollama hardware acceleration.
Executes desktop scripts, parses spreadsheets, or fills local database records.
Runs entirely behind your physical corporate firewall without transmitting data to external servers.
Indexes local PDFs, CAD files, code bases, and financial records in lightweight encrypted local databases.
Automates repetitive desktop software interactions, file transformations, and offline reporting.
Leverages existing local GPU workstations to eliminate recurring cloud API token usage expenses.
import requests
def query_airgapped_agent(prompt: str, local_context: str):
response = requests.post(
"http://localhost:11434/api/generate",
json={
"model": "llama3.3:70b-instruct-q4_K_M",
"prompt": f"Context: {local_context}\n\nTask: {prompt}",
"stream": False,
"options": {"temperature": 0.1}
}
)
return response.json()["response"]
# Executed 100% offline
print(query_airgapped_agent("Summarize contract terms", "Non-Disclosure Agreement Clause 4..."))We deploy optimized local agents on standard workstation hardware equipped with modern GPUs (such as NVIDIA RTX 4090 / L40S or Apple Silicon M2/M3 Max Mac Studio).
Yes. All parsing, text extraction, embedding generation, and LLM inference occur locally in system memory without network calls.
Book an architecture review session with our senior AI engineers to assess your infrastructure and custom requirements.
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