Build · Integrate · Automate · Operate

Custom AI + IoT solutions for connected products

ZedIoT combines hardware, firmware, gateways, platforms, AI workflows, and business-system integration into a practical delivery path. Start with your device and operating goal, then validate the highest-risk link first.

Device retrofitIndustrial IoTAI visionCold equipmentEdge gateway
Private AI and IoT platform deployment for connected device operations
Industrial edge gateway connected inside a control cabinet for equipment monitoring
Solution scenarios

Combine devices, edge gateways, platforms, and AI around real business workflows

Use this section as a routing map. Each card points to the closest solution direction and the pages that help validate it.

AWS IoT cloud services and connected device workflow
03

Connected-product companies, equipment manufacturers, IoT platform teams, and industrial operators

AWS IoT Device and Cloud Operations

Connect device identity, MQTT messaging, edge gateways, AWS IoT Core, event-driven services, applications, and business workflows.

Device identityMQTTAWS IoT CoreEvent routing
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Warehouse recognition workflow with AI vision and WMS integration
04

Warehouse teams, logistics operators, manufacturing inventory teams, and high-value asset managers

AI Vision Warehouse Recognition and Asset Operations

Use AI vision, barcode, RFID, and workstation workflows to close the loop between physical goods and system records.

Identity verificationObject recognitionInventory checksWorkflow evidence
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Fleet management and localization workflow for field operations
05

Logistics teams, fleet operators, factories, smart buildings, and high-value asset managers

Device Localization and Asset Movement Visibility

Use GPS, UWB, BLE, RFID, and sensor fusion to turn asset movement into maps, alerts, dispatch actions, and trusted records.

GPS and geofenceUWB zonesBLE presenceRFID identity
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Bluetooth connected devices in a local smart product environment
06

Connected-product OEMs, smart-device teams, industrial equipment builders, and mobile workflow owners

Bluetooth and BLE Product Connectivity

Build BLE firmware, mobile onboarding, gateway bridges, cloud integration, security, diagnostics, and fleet-ready support as one product path.

BLE firmwareMobile onboardingGateway bridgeLow-power design
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Fleet asset tracking and logistics operations scenario
07

Logistics operators, transportation teams, service fleets, cold-chain operators, and charging station managers

Fleet Management and Smart Logistics Operations

Connect vehicle GPS, cargo status, dispatch, maintenance, charging assets, map dashboards, and reports into one fleet operations platform.

GPS trackingDispatchCargo trackingMaintenance
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AI application workflow for voice AI and connected product use cases
08

Smart hardware teams, service terminal products, industrial device builders, and AI workflow owners

Embedded Voice AI for Devices and Operations

Add ASR, TTS, wake-word, local AI, and voice workflow integration to products that need speech to become a reliable action.

ASR and TTSWake wordOn-device AIPrivate deployment
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Connected beverage cooler and refrigeration monitoring scene
09

Retail chains, convenience stores, refrigeration OEMs, service providers, and cold-chain operators

Refrigeration Monitoring for Chain Stores and Cold Equipment

Monitor beverage cabinets, fresh food cabinets, low-temperature equipment, and distributed store refrigeration remotely.

Temperature monitoringRemote parametersMulti-store managementException alerts
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Edge AI video analytics deployment using an AIHub gateway
10

System integrators, industrial sites, field operations, and AI-enabled device projects

Edge Computing and Gateway Integration

Place protocol conversion, buffering, local rules, and AI inference close to field devices where latency matters.

Store-and-forwardProtocol conversionLocal rulesEdge AI
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IoT hardware bench with modules for smart device retrofit planning
11

Equipment OEMs, smart device brands, industrial product teams, and companies upgrading ordinary devices with AI

AI Hardware and Smart Device Retrofit

Upgrade ordinary equipment with communication modules, voice AI modules, ESP32-S3 controllers, TinyML, firmware, and platform workflows.

Communication modulesESP32-S3Voice AI modulesTinyML
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AI automation workflow connecting business systems and device events
12

Operations teams that need AI assistants, private knowledge, alerts, and workflow automation

AI Workflow Automation for IoT and Business Systems

Connect device events, documents, tickets, and business APIs into AI-assisted workflows that support real operations.

Dify appsn8n automationPrivate knowledgeAlert triage
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Connected home-use medical device workflow supported by an application
13

Medical equipment manufacturers, health-device product teams, laboratories, and equipment operations teams

Connected Medical Equipment and Device Operations

Connect equipment through firmware, host software, middleware, remote operations, IoT platforms, and approved system integration.

Equipment connectivityHost softwareMiddlewareRemote service
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AI-assisted Home Assistant smart facility automation
14

Device brands, commercial facilities, integrators, and connected-product teams

Home Assistant Integration and Automation

Unify ESPHome, Tuya, Matter, MQTT, Zigbee, Node-RED, local control, dashboards, and AI-assisted automation.

ESPHomeMatter and TuyaMQTT and ZigbeeNode-RED
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LoRaWAN industrial equipment monitoring scenario
15

Industrial sites, utilities, agriculture, buildings, and remote asset-monitoring teams

LoRaWAN Field Connectivity

Design low-power sensor networks with realistic coverage, gateway placement, payloads, backhaul, and platform workflows.

Network designSensor firmwareGateway deploymentPayload decoding
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Open-source IoT capabilities for automation, analytics and device management
16

Device companies, integrators, industrial operators, and SaaS teams

Open-Source IoT Platform Ownership

Customize open-source IoT frameworks with device services, dashboards, APIs, private deployment, and maintainable source handoff.

ThingsBoardPrivate deploymentDevice servicesCustom APIs
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Reference architecture

One delivery architecture from device access to business automation

The architecture is modular: use only the device, edge, platform, AI, or integration layers required by the project.

1

Devices and sensors

Collect physical state, control points, events, and operating signals.

Interfaces and point table
2

Embedded control

Run drivers, local logic, communication, diagnostics, and OTA-capable firmware.

Firmware and source package
3

Edge gateway

Handle protocol conversion, buffering, local rules, edge AI, and remote logs.

Gateway and protocol modules
4

ZedIoT platform

Manage devices, roles, alarms, work orders, dashboards, reports, and APIs.

Platform and operations console
5

AI automation

Apply recognition, knowledge search, analysis, and workflow orchestration.

AI models and workflow apps
6

Business systems

Connect ERP, WMS, MES, CRM, helpdesk, or customer-owned platforms.

Business integration loop
Selection guide

Choose the implementation path from device conditions

Start with the interface, controller, network, and workflow constraints. Then validate the highest-risk path before expanding the system.

View development services →
Project conditionRecommended pathMain delivery
Device has RS485 / RS232 or vendor protocolExternal connectivity terminal or gatewayConverter, protocol adapter, platform access
Controller firmware can be upgradedEmbedded connectivity retrofitFirmware, communication, OTA, diagnostics
Multiple brands need unified operationsEdge gateway and device modelProtocol mapping, model design, operations platform
Weak network or local response is requiredEdge computing designLocal rules, buffering, recovery, edge AI runtime
Existing data needs AI automationAI workflow and system integrationLLM apps, workflow automation, business APIs
Implementation path

Validate one critical path first, then scale the solution

Projects can start from one device, one protocol, one AI workflow, or one business integration before full rollout.

  1. 01

    Scenario and device review

    Clarify business goals, device condition, field constraints, and success criteria.

  2. 02

    Protocol and data mapping

    Define interfaces, point tables, data flows, permissions, and integration boundaries.

  3. 03

    PoC validation

    Validate the highest-risk communication, AI, edge, or system-integration path first.

  4. 04

    System development and integration

    Build device, edge, platform, AI, application, and business-system modules in stages.

  5. 05

    Pilot deployment and acceptance

    Test real workflows, abnormal states, recovery, security, and operating handoff.

  6. 06

    Scale and operations

    Support batch rollout, OTA, monitoring, maintenance, documentation, and continuous iteration.

Questions before a solution project

Start with constraints, not assumptions

Even if documentation is incomplete, a sample device, target workflow, and current system boundary are enough to begin evaluation.

Do we need to replace the existing controller?

Not always. We first evaluate serial ports, bus interfaces, extension options, enclosure constraints, and field installation conditions before recommending a retrofit, gateway, or controller upgrade.

Can devices be integrated without complete protocol documents?

Sometimes. We can evaluate sample devices, existing software, packet captures, and field tests, but complete protocol documentation reduces project risk and validation time.

Can different device brands be managed in one platform?

Yes. We use protocol adapters, unified device models, gateways, and platform rules to normalize different brands, models, and operating workflows.

Can the solution connect to ERP, MES, WMS, CRM, or ticketing systems?

Yes. Integration can use APIs, webhooks, message queues, databases, or middleware, with clear rules for direction, permissions, failure retry, and data ownership.

Can AI run on edge devices or inside a private network?

Yes. The right deployment mode depends on model size, latency, privacy, hardware resources, and the operations team that will maintain it.

Can we start with a smaller PoC?

Yes. We usually recommend starting with representative devices and one critical workflow before committing to full platform development or batch rollout.

Talk to ZedIoT

Tell us your device scenario and target workflow

Share your device type, interface, field environment, current software stack, and the business process you want to improve. We will help define a practical solution path.

  • AI + IoT product architecture review
  • Hardware, firmware, cloud, and application integration
  • Prototype planning and production support