IoT Software Development Company
Deploy Smarter Connected Devices with AI at the Edge
We build the firmware and cloud infrastructure to manage fleets of thousands of connected devices securely.
.avif){kind=small}
.avif){kind=small}
%20copy.avif){kind=small}
Award Winning Development
We hire engineers who understand the protocols and compliance requirements that govern your business.
Their team consistently brings thoughtfulness, professionalism, and ownership, making them a valued extension of our internal team.
.avif)
Behind every huge business win is a technology win. So it is worth pointing out the team we've been using to achieve low-latency and real-time GenAI on our 24/7 platform. It all came together with a fantastic set of developers from Azumo.
.avif)
We’ve been working with Azumo since our founding. Their team has been great to work with. We built out a massive AI based data platform with their help. They can handle just about anything.
The work was highly complicated and required a lot of planning, engineering, and customization. Their development knowledge is impressive.
They know a lot about the products they build on and were very responsive. Their project manager broke down barriers and explained all the intricacies of the custom software development effort in a way that was easy to understand.
We invest in our nearshore software engineers and it shows.
Top AI Development Company
Top Software Developers
Top Software Development Company
Impact Company of the Year
Best in the West
Hot Vendor for AI
Technology Expertise
IoT Software Development Company
Transform industries, enhance efficiency, improve decision-making, and enable new opportunities for connectivity and automation.
Bandwidth costs and latency make it impractical to send every sensor reading to the cloud for processing.
78%
55%
43%
IoT Software Development Company
We deploy TinyML models directly onto microcontroller units. These models detect vibration or temperature anomalies locally, triggering alerts without needing constant cloud connectivity.
Predictive Maintenance
Machine learning that forecasts equipment failures enabling proactive maintenance and preventing downtime.
IoT Cloud Platforms
Device management, data ingestion, rule engines, and dashboard visualization for connected devices.
Edge Computing Applications
On-device ML inference, data preprocessing, and local decision-making for latency-sensitive use cases.
LoRaWAN/NB-IoT Integration
Low-power wide-area network connectivity for battery-powered sensors in agriculture and smart cities.
Device Provisioning Systems
Zero-touch provisioning, certificate management, and secure bootstrapping for manufacturing.
Bluetooth Low Energy Apps
Mobile apps for device pairing, configuration, and data sync with BLE peripheral devices.
Industrial IoT Gateways
Protocol translation between Modbus/OPC-UA and cloud platforms with local buffering.
IoT Security Implementation
Secure boot, encrypted communications, and over-the-air key rotation for embedded devices.
Time-Series Data Processing
High-volume sensor data ingestion with time-series databases (InfluxDB, TimescaleDB) for analytics.
IoT Device Firmware
C/C++ firmware for microcontrollers with MQTT/CoAP connectivity and OTA update capability.
IoT Cloud Platforms
Device management, data ingestion, rule engines, and dashboard visualization for connected devices.
Edge Computing Applications
On-device ML inference, data preprocessing, and local decision-making for latency-sensitive use cases.
LoRaWAN/NB-IoT Integration
Low-power wide-area network connectivity for battery-powered sensors in agriculture and smart cities.
Device Provisioning Systems
Zero-touch provisioning, certificate management, and secure bootstrapping for manufacturing.
Bluetooth Low Energy Apps
Mobile apps for device pairing, configuration, and data sync with BLE peripheral devices.
Industrial IoT Gateways
Protocol translation between Modbus/OPC-UA and cloud platforms with local buffering.
IoT Security Implementation
Secure boot, encrypted communications, and over-the-air key rotation for embedded devices.
Time-Series Data Processing
High-volume sensor data ingestion with time-series databases (InfluxDB, TimescaleDB) for analytics.
AI Agents
We can also build intelligent workflows with AI Agents
Trusted Partner
We follow a structured, IoT-first AI development process that prioritizes reliability, edge performance, and operational continuity
STEP. 01
IoT AI Discovery
We understand sensor systems edge computing and operational technology. We design AI that improves reliability and operational efficiency.
STEP. 02
Sensor Data Integration
We integrate data from IoT devices sensors industrial equipment and control systems into AI platforms.
STEP. 03
AI Model Development
Our engineers develop IoT AI including time series models anomaly detection and edge-optimized algorithms.
STEP. 04
Operational Testing
We test AI in real environments validating accuracy latency and reliability before production deployment.
STEP. 05
System Integration
We integrate AI with IoT platforms edge devices and operational systems ensuring real-time performance.
STEP. 06
Continuous Model Refinement
Post-deployment we monitor AI performance equipment health and operational metrics refining models for accuracy.
Benefits
IoT Software Development for AI at the Edge and in the Cloud
Device fleets, sensor networks, and telemetry pipelines require AI built by teams who understand the constraints of embedded systems and the scale of cloud processing.