Deploy secure, autonomous AI & Data Science agents locally on desktop hardware. Avoid cloud subscription leaks and thousands of euros in monthly API token bills.
Auto-correcting agent loops (CrewAI, LangGraph) querying APIs. Millions of input/output tokens daily scale costs exponentially.
Run high-parameter open models (Llama-3.1-70B, DeepSeek) locally in unified memory. Run unlimited agent steps completely free.
Real-time hardware allocation specs for the local **Grace Blackwell GB10 Superchip** on your desk.
Tensor Core computations
Out of 128GB Unified Memory
OpenShell active namespaces
Clicking triggers local offline inference, increasing GPU loads and memory allocations momentarily.
Select an agent security profile preset. OpenShell applies these YAML policies at runtime to sandbox local system interfaces.
OpenShell utilizes Linux **Landlock** filesystem restrictions to prevent AI agents from reading sensitive system directory configurations, ssh credentials, or .env project parameters.
It also hooks the network stack at the process level, allowing network calls to be blocked or routed dynamically.
Select simulated commands to execute from our workspace. Watch the local OpenShell engine enforce policy restrictions.
Estimate the return on investment of deploying local DGX Spark workstations compared to paying cloud LLM subscription APIs.
Investing in a local workstation pays for itself within months, while guaranteeing absolute corporate data privacy.
Understand the execution hierarchy of OpenShell wrapping local CLI agent tasks inside kernel namespaces.
Read automated logs and newsletter drafts compiled locally by the AI agent and pushed directly to Substack via GitHub Actions.
Our data auditor agent audited 10,250 records, identifying and masking 15 social security leaks completely offline. Compute Cost: €0.00.
Status: Draft sent to SubstackThe secure software coder agent refactored core database connections, executed python tests in Landlock, and pushed main branch updates.
Status: PublishedTrigger simulated malicious exploits to evaluate sandbox vulnerabilities. Docker containment escape vectors vs. OpenShell kernel-level blocks.
Docker containers create a virtualized user space but lack native, granular process capability and network egress filters without complex setup. Container escapes are possible if the container is breached or run as root.
**NVIDIA OpenShell** runs natively with zero GPU latency overhead, wrapping the agent locally using Linux Landlock kernel sandboxing.