IoT Platform Development

An IoT platform is the full software stack that connects your physical devices to the applications and people that use their data. It includes: device management (provisioning, authentication, status monitoring, OTA firmware updates), the ingestion layer (message broker, protocol handling, queue management for high-frequency data), the processing layer (stream processing, aggregations, threshold-based alerting, anomaly detection), the storage layer (time-series database for sensor data, relational database for device registry and configuration), and the application layer (REST API, operational dashboards, alert management, and integrations with ERP, CRM, or CMMS). Most organisations start with a managed cloud service and move to a custom platform when the generic service can't handle their specific device management, multi-tenancy, or integration requirements.

We build IoT platforms that communicate with devices via MQTT (the most common IoT messaging protocol, lightweight and well-suited to constrained devices), CoAP (for very constrained devices with minimal power budget), HTTP/REST (for devices with higher power and better connectivity), WebSocket (for bidirectional real-time communication), Modbus (for legacy industrial equipment), and OPC-UA (the standard for industrial automation systems). Protocol support is determined by what your devices use, we build the broker and message handling layer to match your hardware's communication protocol. We also work with AWS IoT Core and Azure IoT Hub as the message broker layer when those are already in your infrastructure.

Device data is high-frequency, time-series, and often bursty, it requires a different architecture than transactional data. We use a message broker (MQTT broker or managed alternative) to decouple ingestion from processing, a message queue to handle burst traffic without data loss, stream processing for real-time aggregations and alerting, and a time-series database (TimescaleDB, InfluxDB, or a managed alternative) for efficient storage and querying of sensor data. We scope the data architecture around your device count, messages-per-second rate, and data retention requirements before writing a line of code.

Security starts at the device. Every device gets a unique X.509 certificate and authenticates over mutual TLS before it can publish, so a compromised device can be revoked without touching the rest of the fleet. Data in transit is encrypted; data at rest sits in access-controlled stores. On multi-tenant platforms, isolation is enforced at every layer: broker ACLs scope each tenant to its own topic namespace, row-level security separates tenant data in the database, and tenant claims are validated on every API call. Where a regime applies, we design to it, GDPR data-residency and retention rules for EU device data, or SOC 2 controls for platforms sold to enterprise buyers.

Yes. Some decisions cannot wait for a cloud round-trip, a safety shutoff or a local alarm has to fire in milliseconds. We push filtering, aggregation, and threshold rules onto edge gateways or the devices themselves, then sync summarised data to the cloud on a schedule or when connectivity returns. This keeps bandwidth and cloud storage costs down, and it keeps the system working when the network drops. OTA updates roll out edge logic and device firmware in stages, with automatic rollback if a device goes offline mid-update.

A focused first version, device management for one device type, real-time data ingestion, a dashboard, and basic alerting, starts around $30,000-$70,000. From there the platform grows to $70,000-$180,000 as you add device types, complex data processing, multi-tenant architecture, ERP integration, and mobile apps. Cost depends on device count, data volume, integration complexity, and multi-tenancy requirements. We scope every project before pricing it and deliver a fixed-cost proposal.