About

About Infersec

Infrastructure-first AI delivery for teams that need control.

Infersec bridges Linux and macOS model hosts to cloud-facing AI API surfaces. Based in the EU, the platform never logs prompts or tool-call content — you keep full ownership of compute and data while delivering compatible endpoints and policy-aware routing.

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icon Main Features

Control plane for secure, composable AI delivery

Connect private hardware, expose compatible APIs, route intelligently — own your AI stack end to end

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OpenAI & Anthropic-compatible endpoints

Drop-in support for existing SDKs and clients without protocol rewrites.

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Connect Linux and macOS hosts

Run conduit workers on your own machines and keep model execution private.

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Intelligent routing with failover

Session stickiness, load balancing, priority routing, and automatic offline-source detection across your inference fleet.

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MCP gateways with database access

Expose MySQL, Postgres, and MariaDB through scoped MCP gateways — attach tool servers per endpoint with policy-aware access controls.

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Privacy-first by design

No prompt logging, no tool-call content storage. Your data stays on your infrastructure in self-hosted deployments.

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Pluggable telemetry

Ship logs, traces, and Prometheus-format metrics to your existing observability stack.

icon Common questions

Frequently Asked Questions

Everything you need to know about running AI endpoints from your own hardware.

Yes. Install the Infersec conduit on any Linux or macOS machine — mini PCs, desktops, Macbooks, rackmount servers. If it can run an inference engine like llama.cpp or vLLM, it can be a source.

Entirely on your own hardware. Infersec never hosts models — it handles routing, endpoint exposure, and policy while your machines do the inferencing. Nothing leaves your infrastructure.

Infersec detects offline sources automatically and reroutes traffic to healthy sources using fallback chains and priority rules. Endpoints stay available even when individual machines drop off.

That depends on your hardware and the model you choose. With a modern GPU or Apple Silicon, local models like Llama, Mistral, and Qwen deliver responses competitive with hosted services — often faster since there's no queue behind other tenants.

For many workloads, yes. Apple Silicon handles 7B–70B parameter models well, and Infersec's routing lets you chain multiple machines together. You won't match the largest proprietary models on every benchmark, but for most agent workflows, internal tools, and day-to-day inferencing, your own hardware is more than enough — and you keep full control of the data.