The only CMMS that ships an on-prem NVIDIA AI server to your plant floor.

OxMaint's AI stack runs on NVIDIA Tensor Core GPUs with CUDA acceleration. That means deep-learning vision models, vibration anomaly detection, acoustic fault classification, and remaining useful life (RUL) prediction all run in parallel at millisecond latency — directly on the floor. Multi-modal models process video, thermal, vibration, and pressure streams simultaneously. The same hardware that powers data-centre AI clusters is sitting in your maintenance closet.

MaintainX runs on shared multi-tenant CPU cloud infrastructure. There is no GPU layer — and there is no path to add one without rebuilding the architecture. The product offers a "CoPilot" feature that assists with procedure text, but it is a text-only LLM assistant, not an AI maintenance engine. It cannot run vision models, cannot process sensor streams in real time, and cannot perform deep-learning predictive analytics.

Defense contractors, pharma plants under 21 CFR Part 11, power utilities under NERC CIP, and any operation that handles export-controlled or classified data cannot send operational records to a vendor's multi-tenant cloud. Regulators require the data to stay inside the perimeter. OxMaint is built for this — the on-prem deployment keeps every sensor reading, PLC tag, work order, and inspection photo on the customer's own infrastructure. We support fully air-gapped installations where the system never touches the public internet.

MaintainX is cloud-only. All operational data flows through the public internet to vendor servers in third-party data centres. There is no air-gap option, no customer-controlled key management at the infrastructure level, and no path to deploy inside a classified network.

Predictive alerts only help if they fire before the failure. High-fidelity vibration, acoustic, and thermal sensors generate gigabytes of data per second on a busy plant. With OxMaint, all of that traffic terminates on the on-prem GPU server — inference runs in 10–20 milliseconds, fast enough to drive real-time control decisions, abort a bad batch, or stop a press before tooling damage. The "data gravity" problem disappears because the data never has to leave the floor to be processed.

MaintainX has to ship every sensor reading to its cloud, run analysis on shared CPU infrastructure, and ship a response back. Real-world round-trips of 200–500 milliseconds are typical. For threshold alerting and work-order routing that latency is acceptable. For real-time predictive control on a production line, it is too slow to act on.

Mines, refineries, ports, offshore platforms, remote utility substations, and many manufacturing plants have intermittent internet. With OxMaint, the on-prem AI server is the system of record — the platform runs on local hardware whether the WAN link is up or down. Work orders continue, AI inference continues, PM schedules fire on time, and any cloud sync resumes automatically when connectivity returns.

MaintainX has a mobile offline cache so technicians can fill in a work order without signal, but the core CMMS is a cloud application. When the site loses connectivity, the central system goes dark — dashboards do not update, AI features stop, integrations break, and any team member on the web app sees a connection error.

OxMaint sells a turnkey AI rollout — not a SaaS subscription. The bundle includes the NVIDIA AI server, cabling, network integration, PLC/SCADA taps, model training on your data, operator and technician training, and 24×7 remote monitoring of the edge box by our SRE team. The site goes live in 6–12 weeks under a fixed scope: weeks 1–4 ship and network, weeks 5–8 train models and pilot, weeks 9–12 go-live and handover. At scale, the economics are CapEx + flat licence — predictable, not per-seat.

MaintainX is sold as a per-user-per-month subscription. The capabilities a serious plant needs — IoT/PLC connectivity, SAP integration, advanced analytics — sit in higher tiers or as paid add-ons. Hitting feature parity with what OxMaint includes out of the box pushes the real per-seat cost well above the listed sticker.