Generate IoT Architecture Diagrams with AI

Visualize your complete IoT system — from edge devices and field gateways through MQTT brokers, device management, time-series data ingestion, stream processing, and cloud analytics dashboards. Describe your IoT stack in plain English and get a professional architecture diagram for documentation, team onboarding, or architecture reviews.

The challenge

IoT architectures span physical and digital layers that are hard to communicate without a clear diagram: field devices (sensors, PLCs, embedded systems) connect through edge gateways that handle local processing and protocol translation, then transmit to cloud ingestion endpoints over MQTT, AMQP, or HTTP. The cloud layer adds device management (provisioning, OTA updates, shadow state), time-series storage (InfluxDB, TimescaleDB, AWS Timestream), real-time stream processing (Apache Flink, AWS Kinesis), and analytics dashboards. Security — TLS certificates, device authentication, network segmentation — runs through every layer. Drawing this architecture by hand is time-consuming and notoriously hard to keep current as the device fleet evolves.

The solution

Describe your IoT stack in plain English and get an accurate architecture diagram in seconds:

"Smart factory IoT architecture. Edge layer: 200 CNC machines with Siemens S7 PLCs, connected to 10 edge gateways (Raspberry Pi 4 running Balena OS). Edge gateways: collect OPC-UA telemetry from PLCs every 100ms, apply edge filtering (discard no-change readings), buffer 5 minutes of data locally, forward to cloud over MQTT via AWS IoT Core. Device management: AWS IoT Core manages device certificates (X.509), job execution for OTA firmware updates, device shadow for current machine state. Ingestion: AWS IoT Rules Engine routes telemetry to Kinesis Data Streams. Stream processing: Apache Flink (on EMR) calculates rolling averages, detects anomalies (3-sigma rule), writes alerts to SNS. Storage: raw telemetry to InfluxDB (TimescaleDB on RDS as backup). Analytics: Grafana dashboards showing real-time machine utilization, downtime prediction, and energy consumption. Alerts: SNS → PagerDuty for critical anomalies."

From that description, you get a complete IoT architecture diagram showing the device-to-cloud data path, all components, and the security and management layers. Use chat to add a digital twin layer, map the OTA update flow, or annotate network segmentation zones.

IoT diagrams we support

Industrial IoT (IIoT) architectures
Factory floor connectivity — PLCs, OPC-UA, SCADA systems, edge gateways, protocol bridging (OPC-UA → MQTT), and cloud ingestion for predictive maintenance and OEE analytics.
Smart building and energy systems
HVAC, lighting, access control, and energy meter networks with BACnet/Modbus integration, building management systems, and cloud energy management platforms.
Consumer IoT and connected products
Mobile app + device connectivity architectures — BLE/Wi-Fi device pairing, AWS IoT or Google Cloud IoT Core device management, OTA update pipelines, and user-facing dashboards.
Edge AI and inference at the edge
Architectures where ML inference runs on edge devices (TensorFlow Lite, ONNX Runtime on NVIDIA Jetson), with model management, federated learning coordination, and cloud model update pipelines.

Perfect for

IoT platform architecture design reviews
Security assessments — mapping trust boundaries and device authentication
Regulatory compliance documentation (IEC 62443, NIST IoT guidance)
Onboarding embedded engineers to the cloud platform layer
Customer-facing architecture documentation for IoT product deployments
Evaluating managed IoT platforms (AWS IoT Core vs Azure IoT Hub vs Google Cloud IoT)

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