Devices built around basic rule-based logic when the use case actually needs real-time, on-device intelligence
Cielo’s smart devices, powered by Inabia’s IoT solutions, transform air-conditioning systems — enabling remote control and seamless integration with smart-home platforms like Alexa and Google Home.
A sensor that can detect an anomaly is only useful if it can act on that detection fast enough to matter. A factory floor losing milliseconds to a round trip to the cloud isn’t catching defects in real time — it’s catching them after the fact.
Connectivity alone was the IoT story for the last decade. The story now is intelligence: devices that can sense, decide, and act locally, without waiting on a network connection that might lag, drop, or simply not be fast enough for what the use case actually demands.
Inabia builds IoT systems engineered for that shift — combining hardware integration, edge intelligence, and cloud architecture into connected products that don’t just collect data, but actually act on it.
Talk to our IoT team today →Six faults — and the layer of the stack each one actually sits in.
Devices built around basic rule-based logic when the use case actually needs real-time, on-device intelligence
Cloud-only architectures that introduce latency exactly where milliseconds matter — predictive maintenance, autonomous equipment, safety-critical monitoring
Security treated as an afterthought, when a single compromised device can expose every other device on the same network
No real OTA (over-the-air) update strategy, leaving deployed devices stuck on outdated firmware and unable to receive security patches or new capability
Hardware and software built in isolation instead of as one coherent system, creating integration problems that surface only after deployment
A pilot that works in a lab but was never architected to scale to hundreds or thousands of devices in the field
A connected device that can’t act on what it senses, can’t be updated securely, and can’t scale past a pilot isn’t really delivering on what IoT is supposed to do for your business.
On-device intelligence that reacts in real time, not after a round trip to the cloud
A security architecture built on zero-trust principles, so one compromised device doesn’t put the entire network at risk
Reliable OTA update infrastructure, so devices in the field stay current, secure, and capable of new functionality over time
Architecture genuinely built to scale from a handful of pilot devices to a full fleet deployment
A cloud layer focused on what it should actually be doing — coordination, long-term analytics, and model training — instead of handling every routine decision
Seven service areas across device, edge and cloud — architected together rather than handed between vendors.
Before any hardware gets built, we design the end-to-end architecture across device, edge, and cloud layers, so the system is built to scale from the start instead of needing a rebuild after the pilot succeeds.
Custom firmware for microcontrollers, RTOS, and bare-metal systems, built for the specific constraints of your hardware rather than a generic template.
Sensor acquisition, calibration, and real-time data fusion, alongside PCB design and rapid prototyping to get from concept to working hardware faster.
Object detection, anomaly detection, predictive maintenance models, and other inference workloads deployed directly on-device, reducing latency, cutting bandwidth costs, and keeping systems operational even when connectivity drops.
WiFi, BLE, LoRa, Zigbee, NB-IoT, cellular, and increasingly private 5G for industrial deployments — matched to the range, power, and reliability your specific use case actually requires.
Real-time device monitoring, fleet management, and analytics dashboards that give you actual visibility into a deployed fleet, not just raw data nobody’s looking at.
Zero-trust device authentication and secure, reliable over-the-air update pipelines, so your fleet stays patched and current without requiring a truck roll to every device.
Full-stack expertise across hardware, firmware, edge AI, and cloud, so you’re not coordinating between three separate vendors
Security architecture built in from day one, not retrofitted after a vulnerability surfaces
Edge AI capability that turns raw sensor data into real-time decisions, not just a stream of numbers
Architecture designed to scale from pilot to fleet deployment without requiring a rebuild
Deep domain experience across manufacturing, logistics, healthcare, and smart infrastructure
Six phases — the strip below each one showing how much of the build is behind you.
We understand the real-world problem the device needs to solve, and what “fast enough” actually means for your specific application
A coherent design across device, edge, and cloud layers, planned for fleet-scale deployment from the start
Hardware and firmware built and tested together, validating the concept before committing to full-scale production
On-device models for the inference your use case needs, balancing accuracy against the real constraints of embedded hardware
Cloud connectivity, dashboards, and zero-trust security architecture built around the full system, not bolted on at the end
Fleet rollout supported by reliable OTA update infrastructure, so the system keeps improving and stays secure long after initial deployment
Manufacturers looking to move from reactive maintenance to predictive, a market growing at roughly 35% annually because the cost savings are real
Logistics and supply chain operations needing real-time visibility into distributed assets
Healthcare organizations building connected monitoring devices
Smart infrastructure and smart city initiatives
Any business whose current IoT pilot worked in the lab but has stalled trying to scale into a real fleet deployment
A device that simply reports data back to the cloud is table stakes now. The businesses getting real value from IoT in 2026 are the ones building systems that can sense, decide, and act — reliably, securely, and at scale.
The end-to-end process of building connected devices and systems, covering hardware design, embedded firmware, wireless connectivity, edge intelligence, and cloud integration, so physical devices can sense, communicate, and increasingly act on real-world data.
Cloud-based IoT sends raw data to centralized servers for processing, which introduces latency and depends on a stable connection. Edge AI processes and makes decisions directly on the device or local hardware, enabling real-time response even when connectivity is limited or unavailable, which matters significantly for use cases like predictive maintenance or autonomous equipment.
Simple IoT solutions, like basic single-purpose devices, typically take 3 to 6 months. Industrial platforms, connected healthcare systems, or larger fleet deployments often require 6 to 18 months, accounting for hardware-software integration, security architecture, and staged rollout.
Yes. Because connected devices share a network, a single compromised device can expose others on the same system. IoT security spending is projected to roughly quadruple by the end of the decade, reflecting how seriously the risk is being taken across the industry.
We work across the full stack — hardware integration, sensor selection, PCB and prototyping support, firmware, edge AI, and cloud architecture — so the device and the software running on it are designed as one coherent system rather than handed off between disconnected teams.
Cost depends heavily on hardware complexity, the scope of edge intelligence required, and fleet scale. Engagements typically start in the low five figures for focused projects, with industrial or large-scale deployments running significantly higher. We scope this transparently based on your specific use case and hardware requirements.