Secure inferencing from your own Linux and macOS hardwareExpose secure AI endpoints from your own hardware
Infersec lets teams publish OpenAI and Anthropic-compatible endpoints while keeping model execution on private infrastructure. Route traffic across local and remote sources, compose MCP/tool stacks, and keep every request, prompt, and tool call auditable.
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How it works
Bring your own hardware, deliver cloud-grade AI APIs
A practical rollout path from private model hosts to secure, compatible, and observable inference endpoints.
Step 1
Connect your hardware
Install the Infersec conduit on Linux or macOS hosts connected to your model runtimes.
Step 2
Compose routing rules
Define routing by latency, source health, fallback order, and endpoint-level policy.
Step 3
Publish secure endpoints
Expose OpenAI and Anthropic-compatible endpoints so existing SDKs work immediately.
Step 4
Operate with audit + telemetry
Review auditable prompt and tool-call trails, then ship telemetry to your preferred sinks.
Main Features Control plane for secure, composable AI delivery
Connect private hardware, expose compatible APIs, route intelligently, and operate with full audit visibility
OpenAI & Anthropic-compatible endpoints
Drop-in support for existing SDKs and clients without protocol rewrites.
Connect Linux and macOS hosts
Run conduit workers on your own machines and keep model execution private.
Composable routing rules
Run fallback, balancing, and priority routing across multiple sources.
Composable MCP/tool stacks
Attach tool servers per endpoint with policy-aware access controls and isolation.
Auditable prompts and tool calls
Inspect prompt and tool execution trails for security, debugging, and review.
Pluggable telemetry
Ship logs, traces, and metrics to your existing observability stack.
Policy-first routing and operationsKeep execution private while shipping cloud-grade AI APIs
Infersec gives you endpoint-level routing policies with fallback chains, source priorities, and health-aware failover. Teams can route traffic across local and remote inference sources without changing client integrations.
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Auditable execution trail
Capture prompt and tool-call activity by endpoint, source, and credential context. Keep a defensible audit trail for debugging, compliance, and incident response.
Composable MCP stacks
Attach MCP servers and tool providers per endpoint, enforce scoped access, and evolve your agent runtime in layers instead of one monolithic deployment.
Compatibility matrix
Integrate with your current stack, no protocol rewrite
Infersec is built for teams that need cloud-facing AI endpoints while keeping model execution and policy ownership on their own infrastructure.
| Surface | Support |
|---|---|
| API compatibility | OpenAI Responses + Chat Completions |
| API compatibility | Anthropic Messages |
| Hardware agent OS | Linux and macOS worker hosts |
| Inference sources | Local runtimes and remote providers through one route policy |
| Telemetry | Pluggable telemetry sinks for logs, traces, and metrics |
Need architecture help? Talk to the Infersec team
Share your stack and rollout goals. We will map endpoint compatibility, routing policy, and audit coverage with you.
Start with a guided rolloutReady to design your endpoint policy?
Book an architecture session to map hardware connectivity, routing policy, MCP/tool composition, and telemetry requirements.
Request architecture session