ZEKLARIndustry
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Hardware· manufacturing

FLUX

The in-situ system with IoT and edge AI.

FLUX is Zeklar's in-situ system: it combines an IoT gateway with edge AI to process data where it is generated. It collects field sensor signals, runs predictive analytics on site and forwards only what matters to upstream systems. Available in Basic, Pro and Enterprise tiers to scale from a single cabinet to a whole plant.

3 tier BASIC, PRO, ENTERPRISEIn-situ ON-SITE PROCESSINGOffline ANALYTICS WITHOUT NETWORKADVISORY MODE · READ-ONLY3 tier BASIC, PRO, ENTERPRISEIn-situ ON-SITE PROCESSINGOffline ANALYTICS WITHOUT NETWORKADVISORY MODE · READ-ONLY
01In figuresFIELD DATA
3 tier
Basic, Pro, Enterprise
In-situ
On-site processing
Offline
Analytics without network
02Composition
What's insideIn-situ edge gateway · Basic / Pro / Enterprise
01NPU02RF03I/O04BUF05PWR06IP65

Hover a component

NPU01 / 06

SoC + accelerator

ARM + NPU · 26 TOPS

Edge processing with an NPU for local inference: the decision stays on site.

03The problem

Too many sensors, too little context

Plant sensors produce continuous streams that saturate networks and reach the center already stale. Sending everything raw to the cloud costs bandwidth and delays decisions exactly when a fault is emerging. The analysis has to move on site, next to the machine.

04What it does04
01

IoT gateway

Aggregates thousands of points from heterogeneous industrial protocols and normalizes them into a single data model.

02

Edge AI

Models inferred locally on an accelerator, with no dependence on connectivity to the center.

03

Predictive analytics

Anomaly detection and remaining-useful-life estimation from vibration, temperature and current signatures.

04

Store-and-forward

Buffers data during network outages and syncs it in order once the link returns.

05How it works04 STEPS
01

Connect

Wire field sensors and buses to the FLUX gateway close to the asset being monitored.

02

Model

Define tags and deploy the predictive models trained on MONOLITH with CORTEX.

03

Analyze

The edge AI evaluates signals in real time and produces local indicators and alarms.

04

Forward

Only relevant events and aggregates are pushed to PULSE and archived in VAULT.

06Architecture

FLUX is the in-situ system that combines an IoT gateway with edge AI: it collects field signals, normalizes them, runs predictive analytics on site and forwards only relevant events and aggregates to PULSE and VAULT. The architecture is layered, from multiprotocol acquisition to accelerator-based inference, with store-and-forward to operate even without a network.

01Multiprotocol acquisitionInterfaces to heterogeneous industrial buses and protocols (OPC UA, MQTT, Modbus) that aggregate thousands of sensor points into a single data model.
02Normalization and taggingRaw signals are typed, timestamped and mapped to semantic tags, making the data comparable and ready for models.
03Edge AI inferenceAn NPU/GPU accelerator runs locally the models trained on MONOLITH with CORTEX: anomaly detection and remaining-useful-life estimation without depending on the center.
04Store-and-forwardA persistent local buffer holds data during network outages and syncs it in order, losslessly, when the link returns.
05Forwarding and integrationOnly relevant events, alarms and aggregates are pushed to PULSE for operations and to VAULT for history, cutting bandwidth and latency.
07Specifications
CPUARM/x86 industriale multi-core
AI acceleratorNPU/GPU edge (fino a ~40 TOPS)
RAM4-32 GB (per tier)
Buffer storage64 GB-512 GB eMMC/SSD
Field I/OGbE, RS-485, CAN, DI/DO, 4-20 mA
Power9-36 VDC
Operating range-20/+60°C
Ingress ratingIP65 (Pro/Enterprise)
08Deployment

DIN-rail in cabinet

DIN-rail gateway close to the monitored asset, wired to sensors and field buses, powered from the local panel (Basic tier).

Concentration rack

Rack unit that concentrates many field nodes for a plant section, with greater inference and buffer capacity (Pro tier).

Ruggedized in situ

Fanless IP65 chassis for direct installation on machinery in harsh environments, resistant to dust, humidity and vibration (Enterprise tier).

09Security & compliance

Verified boot

Secure boot and TPM 2.0 ensure the gateway only starts signed firmware and models, anchoring node identity to the Zeklar network.

Encrypted buffer

The store-and-forward buffer is encrypted at rest: data held during an outage stays protected even if the device is tampered with.

mTLS channels and RBAC

Forwarding to PULSE and VAULT runs over mTLS; identity and entitlements come from AEGIS with role-based access control and audit.

Certifications

ISO 27001-aligned management; hardware with CE marking and industrial EMC (EN 61000-6-2) for plant environments.

10Integrations
PULSE for alarms and operationsCORTEX for model trainingVAULT for signal historyCORE as a downstream control nodeField OPC UA, MQTT and Modbus
11FAQ

What is the difference between FLUX and CORE?

FLUX is the IoT gateway and edge AI that collects and analyzes field signals; CORE is the downstream control node. They often work together, with FLUX upstream.

What happens if the network drops?

FLUX keeps acquiring and analyzing locally and buffers the data; on reconnection it syncs it in order and losslessly to PULSE and VAULT.

How do predictive models reach the device?

They are trained on MONOLITH with CORTEX and pushed to FLUX as signed artifacts, executed locally on the AI accelerator.

What signals does it analyze for predictive maintenance?

Typically vibration, temperature and current, from which it derives anomaly detection and remaining-useful-life estimation.

Does it really reduce network load?

Yes: instead of sending raw streams to the center, it forwards only relevant events and aggregates, cutting bandwidth and decision delay.

12The markGRID 64 · STROKE 5

The mark encodes the mechanism, not the sector: la catena di giunti: il braccio che si articola.

44302216
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