On-site AI inference keeps model execution in your environment so sensitive manufacturing and business data does not need to leave the building. Hexis designs and operates private inference as infrastructure, not as a novelty demo.
Why on-site AI inference matters
Manufacturers and regulated operators increasingly refuse to send core production data to whoever has the newest API. On-site AI inference answers that constraint without abandoning modern models.
Moreover, private hosting supports hexis ERP Link, custom agents, and shop-floor vision where latency and sovereignty both matter.
- Model execution stays local or in a private host you control
- Fits proprietary ERP and plant data
- Supports agents and tools without forcing public cloud paths
- Pairs with open-source stacks when that is the right call
Where on-site AI inference fits the portfolio
Think of on-site AI inference as the backbone under hexis ERP Link, custom agents, hexis PLC instrumentation, and serious AI Accelerator builds. Without a place for models to run safely, every other layer becomes a slideshow.
However, not every workload needs local GPUs. We recommend on-site AI inference when data sensitivity, connectivity, or policy actually requires it, especially on the shop floor.
Open source and anti lock-in
We favor composable, client-owned designs. Tokens get more expensive and the best model changes often. Locking yourself into one proprietary cloud path is a strategic risk.
Likewise, open-source and privately hosted options can reduce forced hardware churn when they are engineered correctly.
Next step
If your data cannot leave the building, on-site AI inference is not optional theater. It is infrastructure. Talk with us about where private execution belongs in your stack.
