When a turbine bearing develops a defect frequency signature that crosses a safety threshold, your DCS registers the condition in under 100 milliseconds. If your AI analytics platform is cloud-based, that data travels from the DCS to a data historian, through a DMZ firewall, across your corporate WAN, to a cloud server in another city or country, through an inference engine, and back again — in 200ms to 1 second under ideal conditions, and not at all during a WAN outage. Edge AI inference eliminates every hop outside the plant perimeter. The inference runs on an NVIDIA GPU server physically located inside your control building — receiving sensor data directly from the DCS over OPC-UA, running AI fault detection in under 10 milliseconds, and triggering alarms and work orders before the next DCS scan cycle completes. No cloud. No WAN. No data leaving the plant. Book a free edge AI architecture review.
Quick Answer
iFactory deploys NVIDIA DGX, EGX, and Jetson edge servers inside your plant perimeter to run all AI inference on-premise — fault detection, performance analytics, digital twin simulation, and CMMS integration — with sub-10ms latency, zero cloud dependency, full offline capability, and NERC CIP compliance by architecture, not by configuration.
Why Edge AI Is the Only Architecture That Works at the Equipment Level
Cloud AI analytics are designed for business intelligence — dashboards, trend reports, monthly analysis. Edge AI is designed for equipment protection — real-time fault detection at the speed of the DCS scan cycle, with inference local to the machine being monitored. These are different problems requiring different architectures. Book a demo to see iFactory's edge architecture applied to your plant.
NVIDIA Jetson — Inference at the Equipment
<10msAt the Machine
NVIDIA Jetson modules mount in the field — on pump skids, in switchgear rooms, at compressor stations — running AI inference locally on the equipment being monitored. A Jetson connected to a boiler feed pump's vibration sensors runs bearing defect frequency analysis in under 10ms, without any data leaving the local equipment network. When combined with NVIDIA EGX zone servers and DGX central compute, Jetson creates a three-tier edge architecture where AI inference occurs at the closest possible point to the sensor.
AI inference at the sensor — zero network hops to cloud
OT Network Isolation — No Data Crosses the ESP
ZeroEgress Ever
iFactory's edge architecture integrates with your OT network via read-only OPC-UA connections — no write access to DCS or protection systems, no data traversing the Electronic Security Perimeter, no internet connectivity required. All AI compute, all model storage, and all data retention stays within the OT or plant network zone where the sensors live. NERC CIP-005 Electronic Security Perimeter compliance is structural — there is no configuration that could cause data egress because no external connection exists.
No egress by architecture — no config can create a violation
3,000+ Parameters Per Second — GPU Parallelism
GPUvs CPU Sequential
A CPU-based edge server processes AI inference tasks sequentially — bearing analysis on machine 1, then machine 2, then machine 3. By the time it reaches machine 200 in a 200-machine fleet, the data from machine 1 is already stale. NVIDIA DGX GPU parallelism processes all 3,000+ parameters from all 200+ machines simultaneously — every machine analysed on every DCS scan cycle, with no queue delay. This is why GPU edge compute is the only architecture that scales to full plant monitoring without sampling.
All 200+ machines analysed simultaneously — no queue, no sampling
Full Offline Operation — WAN-Independent
100%Offline Capable
Cloud analytics platforms have a hidden single point of failure: internet connectivity. A WAN outage, ISP disruption, or cloud provider incident silently disables AI monitoring while the plant continues operating. iFactory's edge architecture has no internet dependency — all AI models, all inference engines, all alarm logic, and all CMMS integrations run on the local plant network. Fault detection and work order creation continue during any external network failure without degraded capability or manual fallback.
WAN outage has zero impact — monitoring never degrades
Digital Twin Simulation — On-Premise GPU
Real-timePhysics Simulation
Physics-based digital twin simulation of your turbines, boilers, and heat recovery systems requires GPU compute that only on-premise NVIDIA DGX hardware can provide at production data rates. Cloud simulation introduces 200ms–1s round-trip latency — making real-time what-if analysis and operational optimisation impossible for fast-moving process conditions. iFactory's on-premise DGX runs digital twin simulation continuously, updating the virtual plant model on every DCS scan cycle and providing optimisation recommendations before the next operator action.
Digital twin updated every DCS scan cycle — not every cloud batch
Air-Gap Compatible Model Updates
OTPatch Process Compatible
iFactory AI model updates are delivered as encrypted update packages through your existing OT change management process — USB media, secure file transfer to a DMZ staging server, or internal network push — with no internet connection required at any stage. Model update packages are signed, hash-verified, and delivered on the same approval and testing cycle as any other OT software patch. Your change management team controls every model update; iFactory never maintains a persistent external connection to push updates autonomously.
Model updates through OT change management — no persistent external connection
AI Inference at the Equipment. Not in the Cloud. Not After a WAN Hop. At the Machine.
iFactory's NVIDIA edge architecture connects to your DCS via OPC-UA. Sub-10ms inference latency. Zero data egress. Full offline capability. NERC CIP by architecture. Live in 6 weeks.
iFactory Edge Architecture vs Cloud-Based Competitor Platforms
GE APM, C3.ai, AspenTech Mtell, and SparkCognition all transmit your operational data to cloud infrastructure. The table below addresses the fundamental architectural differences — not style preferences. Book a technical architecture review to compare against your current setup.
| Architecture Factor |
iFactory Edge |
GE APM |
C3.ai |
AspenTech Mtell |
SparkCognition |
| Inference Location & Latency |
| AI inference location | On-premise NVIDIA GPU | GE cloud servers | C3.ai cloud | Aspen cloud | SparkCognition cloud |
| Inference latency per cycle | <10ms — NVIDIA Jetson/DGX | 200ms–1s cloud round-trip | 200ms+ cloud | Batch — minutes | 200ms+ cloud |
| Equipment-level Jetson inference | Field-mounted at machine | Not available | Not available | Not available | Not available |
| Security & Compliance |
| NERC CIP Electronic Security Perimeter | Compliant by architecture | Data egress — violation risk | Data transmitted | Data transmitted | Data transmitted |
| Zero data egress — architectural | No external connection exists | Data leaves facility | Data leaves facility | Data leaves facility | Data leaves facility |
| Air-gap / full offline operation | 100% offline capable | Internet required | Internet required | Internet required | Internet required |
| Scale & Compute |
| Parameters processed simultaneously | 3,000+ GPU parallel | Sampled / batched | Sampled / batched | Batch processing | Sampled / batched |
| Digital twin — real-time on-premise | DGX GPU — every scan cycle | Cloud simulation only | Not available | Not available | Not available |
| Model updates — OT change mgmt compatible | Air-gap media — no internet | Cloud push — internet req. | Cloud push — internet req. | Cloud push — internet req. | Cloud push — internet req. |
Based on publicly available product documentation and architecture disclosures as of Q1 2025. Verify current capabilities with each vendor before procurement decisions.
Our Numbers
<10ms
AI Inference Latency at the Equipment
3,000+
Parameters Processed Per Second — GPU
Zero
Data Egress — No External Connection
100%
Offline Operational Capability
3 tiers
Jetson, EGX Zone, DGX Central
CIP-013
NERC CIP Compliant Through CIP-005
OT
Patch-Compatible Model Update Delivery
6 wks
Edge Deployment to Full Analytics Live
Get a NERC CIP Architecture Review — Does Your Current AI Platform Violate Your ESP?
iFactory's architecture assessment reviews your current or proposed AI analytics platform against NERC CIP Electronic Security Perimeter requirements — identifying any data egress that constitutes a compliance risk before your next audit.
What Our Clients Say
"The latency difference between cloud and edge AI is not an abstraction — it is the difference between detecting a combustion instability event before the protection system trips and detecting it 800ms after. We ran a 90-day parallel evaluation: iFactory edge AI on-premise versus a cloud-based competitor platform receiving the same DCS data feed. The cloud platform had an average inference round-trip of 680ms. iFactory's on-premise NVIDIA inference averaged 8ms. For combustion dynamics, turbine vibration, and flame instability — where the failure mode can progress from detectable to damaging in under 2 seconds — 8ms is protection and 680ms is a post-incident analysis tool. We selected iFactory. The NERC CIP compliance was also non-negotiable; the cloud platform was rejected by our security team before the technical evaluation concluded."
Control & Instrumentation Engineering Manager
1,600MW Combined-Cycle Gas Portfolio — US Gulf Coast
Frequently Asked Questions
QWhat is the difference between NVIDIA Jetson, EGX, and DGX — and which does iFactory deploy at our plant?
iFactory deploys all three tiers depending on plant scale and use case. NVIDIA Jetson is a compact edge module mounted in the field — at equipment skids or in local control panels — for sensor-level inference on individual machines. NVIDIA EGX is a zone-level server located in the control building, aggregating data from a group of machines and running more compute-intensive analytics. NVIDIA DGX is the central plant AI compute node — running digital twin simulation, fleet-wide fault detection, and model training. Hardware sizing is determined during pre-deployment assessment.
Book a hardware sizing review.
QHow does iFactory connect to our DCS without creating an OT security risk?
iFactory connects via read-only OPC-UA from the DCS historian or data gateway — no write access to any DCS component, no connection to control or protection systems, and no data passing through the corporate IT network. The OPC-UA connection is unidirectional data pull, authenticated with certificates, and monitored by your existing OT security tooling. iFactory's edge servers are registered as EACMS assets under NERC CIP-005 within your existing ESP — no new network zones or firewall rules are created in the process control domain.
QCan iFactory's edge AI also feed a corporate portfolio dashboard at headquarters without violating NERC CIP?
Yes — via a one-way data diode from the plant edge system to a corporate reporting layer. Aggregated KPIs (EFOR, OEE, maintenance spend, fault counts) flow outbound from the plant to HQ dashboards through a hardware data diode that prevents any inbound data path. Raw operational sensor data stays inside the ESP. The data diode architecture satisfies NERC CIP-005 requirements for BES facilities — your security team reviews and approves the diode specification during deployment.
Book a data diode architecture review.
QWho owns the NVIDIA hardware — does iFactory lease it or does the plant procure it as a capital asset?
The NVIDIA hardware is owned by the plant and procured through standard capital channels as plant infrastructure — it appears on your asset register, under your maintenance programme, and under your cyber security asset inventory. iFactory provides software, AI models, deployment, and ongoing support. This matters for NERC CIP CIP-002 asset categorisation and for data sovereignty: the servers, and all data on them, belong to you at all times including at contract termination.
Continue Reading
Sub-10ms Inference. Zero Cloud. At the Equipment. NERC CIP by Architecture.
iFactory deploys NVIDIA Jetson, EGX, and DGX inside your facility. OPC-UA read-only DCS integration. Full offline capability. No data egress. Live in 6 weeks.
NVIDIA Jetson at Equipment
<10ms Inference Latency
Zero Data Egress
100% Offline Capable
NERC CIP-005 to CIP-013
