IoT projects fail when teams treat the edge, the network and the cloud as three separate problems. We build them as one system — firmware that knows how the gateway will behave on a flaky link, a broker that knows what the device is allowed to publish, and a data layer that expects the shape and cadence of what's coming in. The result is a fleet you can actually operate, not a demo that works on the bench.
What we build at the edge
Firmware in C/C++, MicroPython, Rust and Zephyr RTOS or FreeRTOS, targeting ESP32, STM32, Nordic nRF, i.MX and Raspberry Pi class hardware. We pick the stack for the job — Zephyr where you need a real RTOS with mature Bluetooth and Thread stacks, FreeRTOS where the vendor SDK expects it, bare-metal C where power and cost dominate, Rust where memory safety on the device is worth the toolchain investment.
Beyond the application logic, we handle the parts that decide whether a device survives contact with the field: power management and sleep budgets, watchdogs and brown-out recovery, secure boot and signed images, provisioning flows that don't require a laptop, and store-and-forward buffers for when the uplink drops. Sensors and actuators are integrated through I²C, SPI, UART, CAN and Modbus where the physical world demands it, with proper timing and error handling rather than blocking loops.
Gateways and connectivity
Between the sensor and the cloud sits a gateway — sometimes a Linux SBC, sometimes an industrial edge computer, sometimes a cellular router running containerised workloads. We build these to be honest about the network: LTE, NB-IoT, LoRaWAN, Wi-Fi, Ethernet and satellite backhaul all behave differently, and the firmware has to reflect that.
Protocols are chosen deliberately. MQTT with TLS and per-device certificates for most fleet telemetry, CoAP where UDP and constrained radios win, HTTPS for less chatty devices, OPC UA where you're bridging industrial PLCs, and Sparkplug B where the plant floor already speaks it. We terminate on brokers we can operate — EMQX, HiveMQ, Mosquitto, or the managed IoT services on AWS, Azure and GCP — and we design the topic hierarchy and ACLs before the first device connects, not after.
Cloud, data and dashboards
Time-series data has its own gravity. We use InfluxDB, TimescaleDB, QuestDB or the cloud-native equivalents (AWS Timestream, Azure Data Explorer) depending on ingest rate, retention policy and query shape. Downsampling, continuous aggregates and cold-storage tiers are designed in from the start so the database doesn't collapse under a year of one-second telemetry.
On top of that sits the operational layer — device registry, digital twins, rule engines, alerting, and dashboards in Grafana, Superset or a custom React front end. For customers already on Zoho or Odoo, we wire IoT events into the business system so a low-fuel alert becomes a service ticket, a threshold breach becomes an inspection order, and a fleet reading becomes an invoice line. Our CRM & ERP implementation practice does the integration work end to end.
Analytics and ML are added where they earn their keep — anomaly detection on vibration signatures, predictive maintenance on motor windings, demand forecasting on cold-chain assets, computer vision on cameras at the edge. We deploy inference to the gateway with TensorFlow Lite, ONNX Runtime or NVIDIA Jetson stacks when latency or bandwidth make cloud inference impractical.
OTA, security and fleet operations
An IoT deployment you can't update is a liability. We build OTA infrastructure that supports staged rollouts, canary cohorts, delta updates for cellular fleets, atomic A/B partitions with rollback, and signed images verified against a hardware root of trust. The same pipeline handles gateway containers via balena, Mender or fleet-managed Docker.
Security is designed for the whole lifecycle. Unique per-device credentials provisioned at manufacture or first boot, X.509 certificate rotation, secure elements (ATECC608, NXP EdgeLock, SE050) where the threat model calls for it, encrypted-at-rest storage on the device, and audit trails that a regulator or an enterprise security team can actually read. For customers in regulated sectors — energy, water utilities, healthcare, financial payment terminals — we align to IEC 62443, NIS2 and the relevant local frameworks.
Where our work lands
Fleet and asset tracking for logistics and mobility operators, with GNSS, driver behaviour, temperature and door-open telemetry feeding both operations and billing. Energy — smart meters, grid-edge sensors, solar and battery monitoring, with utility-grade data flowing into billing and outage-management systems. Industrial IoT on plant floors and in warehouses, bridging legacy PLCs and modern MES / SCADA layers. Agriculture — soil probes, weather stations, irrigation controllers running on LoRaWAN and NB-IoT across large geographies. Consumer and smart-building IoT where the product is the device experience itself.
For BFSI clients — a large part of our book of business — IoT shows up in payment terminal fleets, ATM telemetry, branch environmental monitoring and cash-in-transit tracking. Our BFSI practice understands the certification, uptime and audit expectations that come with that.
Why teams work with us
Redian is CMMI Level 3 appraised and ISO-certified, with delivery centres in India and client work across the USA, UK, UAE, Kenya, Nigeria, Uganda, Tanzania, Rwanda, South Sudan, Cameroon, Saudi Arabia, Canada and Australia. Our engineers are comfortable moving between soldering-iron problems and cloud-architecture problems in the same week — the same team that debugs a bootloader will design the Kafka topic that carries its output.
Most engagements start narrow — a proof of concept on a real device with real connectivity, terminating in a real dashboard — and expand into fleet-scale rollout, integration with the customer's business systems, and long-run operations. Where the customer wants dedicated capacity, our IT staff augmentation model puts embedded, cloud and data engineers directly into their team.
See related work under /case-studies, or get in touch with a device count, a connectivity profile and the outcome you're trying to reach — that's usually enough for a useful first conversation.
