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Redian Software
Cloud & DevOps expertise

IoT — from edge to cloud, end to end

End-to-end IoT — edge firmware, gateways, MQTT, time-series databases, dashboards. For fleet, energy, industry, agriculture and consumer IoT.

Hire IoT engineers See our work
CMMI Level 3 Appraised ISO Certified 200+ enterprises 5 regional hubs 9+ years of delivery
IoT delivery, in numbers

Proof, not promises.

Real benchmarks from production engagements.

  • Edge to cloud

    Full stack

    Firmware · gateway · platform · dashboard

  • MQTT + CoAP

    Standard protocols

    Plus AMQP, OPC-UA for industrial

  • Edge ML

    On-device inference

    TensorFlow Lite, ONNX Runtime

  • Time-series

    Data layer

    InfluxDB, TimescaleDB, Timestream

What we deliver

The capabilities our IoT engineers ship.

Production patterns from real engagements — not a stack-marketing checklist.

  • 01

    Edge firmware

    C/C++, MicroPython, Rust, Zephyr RTOS, FreeRTOS. ESP32, STM32, Nordic, Raspberry Pi targets. OTA update infrastructure.

  • 02

    Connectivity & gateways

    Wi-Fi, LTE/Cat-M, NB-IoT, LoRa, BLE, Zigbee. Edge gateways aggregating sensors and uplinking via MQTT/CoAP.

  • 03

    IoT platform & data

    AWS IoT Core, Azure IoT Hub, GCP IoT, ThingsBoard. Time-series databases (InfluxDB, TimescaleDB), data lake for analytics.

  • 04

    Edge ML

    TensorFlow Lite, ONNX Runtime, AWS Greengrass. Run inference at the edge for anomaly detection, predictive maintenance, computer vision.

  • 05

    Dashboards & analytics

    Real-time dashboards (Grafana, custom React), geospatial maps (Mapbox), historical analytics, alerting infrastructure.

  • 06

    Security & device management

    Device identity, certificate management, secure boot, OTA updates, fleet management, anomaly detection.

Who hires us for IoT

Where this stack fits best.

We've seen the patterns — match yours against the list to find the closest fit to your situation.

  • Fleet & transport

    Asset tracking, telematics, driver-behaviour analytics, predictive maintenance for vehicle fleets.

  • Energy & utilities

    Smart meter inspection, distribution monitoring, solar project tracking, grid telemetry.

  • Industrial IoT

    Manufacturing telemetry, predictive maintenance, quality monitoring, OPC-UA-based factory floor integration.

  • Agriculture & livestock

    Precision farming, soil monitoring, livestock tracking, irrigation control.

  • Consumer IoT

    Smart home, wearables, consumer-product telemetry with companion mobile apps.

How we engage

From brief to production.

Transparent, milestone-driven, with clear owners and timeframes at every stage.

  1. 01Weeks 1–3

    Discovery & design

    Use-case definition, sensor selection, connectivity choice, platform selection, target architecture.

  2. 02Weeks 4–8

    Prototype

    Hardware prototype, edge firmware, gateway, basic cloud ingestion. Field-trial-ready proof of concept.

  3. 03Months 2–6

    Productisation

    Production firmware, OTA infrastructure, fleet-scale cloud platform, dashboards, alerting.

  4. 04Months 4–8

    Field pilot

    Limited-fleet deployment, telemetry quality verification, false-positive tuning.

  5. 05Ongoing

    Fleet rollout & operations

    Phased fleet expansion, device management, ML model improvement, regulatory compliance updates.

IoT in depth

Inside our IoT practice.

The long-form view of how we approach IoT engagements.

IoT, end to end

IoT is where embedded engineering, networking, cloud platforms and data engineering all meet. We deliver across the full IoT stack — edge firmware, gateway aggregation, MQTT/CoAP messaging, time-series databases, real-time dashboards and ML-on-the-edge.

What we deliver

  • Edge firmware — embedded C/C++, MicroPython, ESP-IDF, Zephyr
  • Connectivity — Wi-Fi, LTE, LoRa, NB-IoT, BLE, Zigbee
  • Gateways & protocols — MQTT, CoAP, AMQP, OPC-UA
  • IoT platforms — AWS IoT Core, Azure IoT Hub, GCP IoT Core, ThingsBoard
  • Time-series databases — InfluxDB, TimescaleDB, AWS Timestream
  • Dashboards — Grafana, custom React, Mapbox for fleet tracking
  • Edge ML — TensorFlow Lite, ONNX Runtime, AWS Greengrass

Domains we cover

Fleet & transport (asset tracking, telematics), energy (meter inspection, grid monitoring), industrial (manufacturing telemetry, predictive maintenance), agriculture (precision farming, livestock tracking), consumer IoT.

Why Redian for IoT

What makes our IoT practice different.

Independent reasons clients pick us over freelancers, agencies and large consultancies.

  • Full-stack IoT

    Firmware engineers, cloud engineers, data engineers and ML engineers in one practice. No vendor handoff between layers.

  • Production discipline

    OTA infrastructure, device-identity certificates, secure boot, fleet management — production IoT realities.

  • Multi-protocol fluency

    MQTT, CoAP, AMQP, OPC-UA, BLE, LoRa, NB-IoT. We pick by fit, not protocol religion.

  • Edge ML capability

    Inference at the edge for use-cases where latency, bandwidth or privacy demand it. Not just cloud-only.

Tech & tools

The IoT stack we ship on.

Production tooling — not just languages on a CV.

  • C/C++
  • Rust
  • Python
  • MicroPython
  • ESP-IDF
  • Zephyr RTOS
  • FreeRTOS
  • ESP32
  • STM32
  • Raspberry Pi
  • Nordic nRF
  • MQTT
  • CoAP
  • AMQP
  • OPC-UA
  • BLE
  • LoRa
  • NB-IoT
  • AWS IoT Core
  • Azure IoT Hub
  • GCP IoT Core
  • ThingsBoard
  • Eclipse Mosquitto
  • InfluxDB
  • TimescaleDB
  • AWS Timestream
  • Grafana
  • TensorFlow Lite
  • ONNX Runtime
  • AWS Greengrass
  • Mapbox
Proof from production

A IoT project we can share publicly.

Most of our work is under NDA — this is one we can share.

TransportationIndia

Mobile App for an On-Demand Driver Services Startup — Nasscom-supported

Client · DriverShaab (Nasscom-supported Indian startup)

  • Live

    On-demand driver platform

  • Real-time

    Driver allocation + tracking

  • Nasscom

    Backed startup

Redian built dual mobile apps for a Nasscom-supported on-demand driver platform — letting customers book vetted drivers and giving drivers real-time job allocation and journey tracking.

Tech stack

React NativePHPMySQL
Read the full case study All case studies
Frequently asked questions

Everything you wanted to ask before the call.

Don't see your question? Ask us directly →

What's a typical IoT engagement?

Discovery + prototype (8–10 weeks), productisation (4–6 months), field pilot (2–4 months), fleet rollout (ongoing). Most engagements are 12–18 months end-to-end, then move to operations and continuous improvement.

Which IoT platform should we use — AWS IoT, Azure IoT, or open-source?

AWS IoT for broad ecosystem and global scale. Azure IoT for Microsoft-heavy enterprises and digital twins. ThingsBoard or open-source for sovereignty / cost-controlled deployments. We choose by fit, not vendor margin.

Do you do edge ML / inference-at-the-edge?

Yes — TensorFlow Lite, ONNX Runtime, AWS Greengrass. Best fit when latency, bandwidth or privacy makes cloud inference unviable. Anomaly detection, predictive maintenance, computer-vision-on-device.

What about device security?

Device identity via X.509 certificates, secure boot, encrypted-at-rest storage, OTA-update signing, anomaly detection at the platform layer. IoT security is a deep topic — we treat it as such.

Engage Redian

Ready to ship with IoT?

Tell us the role, the seniority and the time-zone overlap you need — a senior engineer will send three pre-vetted profiles within a week.

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