Hardware products are only as good as the software running on them. The firmware that controls device behaviour, the cloud backend that processes sensor data, the mobile app that gives users visibility into device status, and the over-the-air update infrastructure that lets you improve the product after it ships — these are software problems that require developers who understand both the hardware constraints and the software engineering discipline needed to work within them. Automely provides dedicated embedded software engineers and product engineering teams, onboarded in 7 days.
Dedicated engineers • 7-day onboarding • Firmware, IoT & medical device software • NDA on day one50+
Clients Served
120+
Projects Delivered
7 Days
Average Onboarding
4.9/5★
Clutch / GoodFirms Rating
Embedded software development operates under constraints that standard web and application development does not face: limited RAM and flash storage measured in kilobytes, not gigabytes; no operating system, or a real-time operating system (RTOS) rather than Linux; processing power measured in MHz rather than GHz; power budgets that require aggressive sleep mode management for battery-operated devices; deterministic timing requirements where a missed deadline is not a slow page load but a safety failure. Writing software for these environments requires a different skill set — C and C++ rather than JavaScript, direct hardware register manipulation, interrupt service routine design, and the validation discipline that certifying software for regulated industries demands.
Product engineering services extend this to the full software stack of a hardware product: the firmware on the device, the cloud backend processing device data, the API layer connecting device data to applications, the mobile or web application users interact with, and the manufacturing test software used during production. A hardware product needs all of these layers to work reliably together — and the team building them needs to understand the constraints at every layer simultaneously.
AI is increasingly relevant in hardware products — not in the firmware itself, but in the cloud processing layer. Machine learning models running on device telemetry data for predictive maintenance, anomaly detection, and usage pattern analysis. Computer vision models processing camera or sensor data in the cloud. AI-powered dashboards that surface actionable insights from device fleet data rather than raw telemetry. Automely's AI engineering capability applies directly to the cloud layer of hardware products.
WHAT WE BUILD
Every product engineering engagement is scoped around your hardware — target MCU, connectivity requirements, regulatory certification pathway, and the full software stack the product needs to reach production.
Firmware development for microcontrollers and microprocessors: bare-metal C/C++ firmware, RTOS-based firmware (FreeRTOS, Zephyr, ThreadX), peripheral driver development (UART, SPI, I2C, CAN, USB, Ethernet), bootloader development and secure boot implementation, over-the-air (OTA) firmware update infrastructure, low-power mode management for battery-operated devices, and watchdog timer and fault recovery logic. Experience with ARM Cortex-M, ESP32, STM32, Nordic nRF52 series, and NXP i.MX families.
Build Your Firmware →End-to-end IoT software: device-side firmware with MQTT, CoAP, or HTTPS connectivity; cloud IoT platform integration (AWS IoT Core, Azure IoT Hub, Google Cloud IoT); device provisioning and certificate management at manufacturing scale; real-time telemetry pipelines from device to dashboard; over-the-air update orchestration; device shadow and twin management for offline-capable devices; and the web or mobile dashboard that makes device data visible and actionable to end users.
Build Your IoT Platform →Software development for regulated medical devices: IEC 62304 software lifecycle process compliance, Software of Unknown Provenance (SOUP) management, risk management integration (ISO 14971), design history file documentation, verification and validation test protocol development, cybersecurity requirements for connected devices (FDA pre-market guidance alignment), and software architecture for Class II and Class III medical devices. Experience with FDA submission support documentation and CE marking technical file requirements.
Build Your Medical Device Software →Full software stack engineering for digital hardware products: firmware plus cloud backend plus mobile or web application developed as an integrated programme. API design connecting device telemetry to application features, user account and device pairing flows, fleet management dashboards for enterprise device deployments, analytics pipelines for product usage and performance data, and the CI/CD infrastructure for both cloud and firmware components. End-to-end ownership of the software layers so hardware engineers can focus on the electronics.
Start Your Product Engineering →Automated testing infrastructure for embedded software: Hardware-in-the-Loop (HIL) test framework development, unit testing for embedded C/C++ using Ceedling/Unity, static analysis integration (PC-Lint, Polyspace, SonarQube), requirement traceability matrix maintenance, regression testing automation for firmware releases, boundary condition and fault injection testing, and the test documentation required for IEC 62304 or DO-178C certification.
Build Your Test Infrastructure →Architecture and technical strategy for hardware product software: embedded software architecture reviews for products approaching scale, connectivity protocol selection (Bluetooth LE, Wi-Fi, Thread, Zigbee, LTE-M, NB-IoT) with power and cost analysis, OTA update strategy design, security architecture for connected devices, manufacturing test strategy, and technical due diligence support for hardware product companies raising investment or preparing for acquisition.
Get Technical Advice →HOW WE WORK
Six stages built around the specific requirements of hardware product software — from hardware discovery and firmware architecture through cloud integration, application development, and certification support.
01
We review your hardware specification, target MCU/MPU, power constraints, connectivity requirements, and certification targets. We map the full software stack needed — firmware layers, cloud backend, mobile or web app — and identify the regulatory requirements that will govern the development process. Deliverable: Software architecture specification with hardware interface definitions and certification pathway plan.
02
We define the Board Support Package (BSP), peripheral driver architecture, RTOS task structure, memory map, and communication protocol stack before any implementation begins. For regulated products, we establish the software development lifecycle documentation framework required by IEC 62304 at this stage. Deliverable: Approved firmware architecture, driver interface specifications, and development environment configured for your target hardware.
03
Peripheral driver development, RTOS task implementation, communication stack integration (Bluetooth, Wi-Fi, cellular), power management, OTA update infrastructure, and bootloader. Unit tests written alongside implementation using Ceedling/Unity. For IEC 62304 projects, verification evidence captured per software safety class requirements. Deliverable: Firmware releases at agreed sprint cadence with passing unit test suite and version-controlled source.
04
Device connectivity backend on AWS IoT Core or Azure IoT Hub — device provisioning, MQTT telemetry ingestion, time-series storage, device shadow / twin management, OTA update orchestration, and the REST or GraphQL API that applications use to query device data and send commands. Deliverable: Deployed backend with device integration tested against physical hardware, with API documentation.
05
Mobile app (React Native) or web dashboard (Next.js) — device pairing flow, real-time telemetry display, alert configuration, device management for fleet operators, and user account management. For enterprise IoT deployments, fleet management dashboards with device health monitoring, firmware version tracking, and bulk OTA update management. Deliverable: Working application connected to live device data, tested on target platforms.
06
System-level testing against requirements (HIL testing where applicable), boundary condition and fault injection testing, performance testing under production load. For medical devices: verification and validation protocol execution, SOUP documentation completion, design history file review. Deliverable: Validated firmware and application suite, complete technical documentation, and a maintained development environment with your team onboarded.
Hardware product software projects fail when the development team does not understand embedded constraints — web developers writing cloud backends without understanding device data volumes, firmware delivered without OTA infrastructure, and medical device software built without the IEC 62304 documentation framework. Automely builds for how embedded systems actually work.
The Problem You Face
What Automely Does Differently
Web or mobile developers hired to build the 'app side' of the product write cloud backends and mobile apps without understanding the firmware constraints — timing assumptions, memory limitations, and connectivity loss handling differ fundamentally from web development
We build firmware and application layers as an integrated programme — the cloud backend is designed around the device's actual data model, and the mobile app handles connectivity loss, device pairing edge cases, and real-time telemetry the way the firmware actually delivers it
OTA firmware update infrastructure added as an afterthought after launch — often requiring devices to be recalled or manually reflashed because the update mechanism was not designed into the firmware from the start
We design OTA update infrastructure — bootloader, dual-bank flash layout, update verification, rollback on failure — into the firmware architecture from the beginning, so products can be updated safely in the field from day one
Medical device software development started without IEC 62304 documentation framework — validation evidence, SOUP inventory, and software safety classification retroactively applied to code that was not written with traceability in mind, requiring expensive rework before regulatory submission
We establish the IEC 62304 software development lifecycle structure at the architecture stage — requirements traceability, SOUP management, and verification evidence captured continuously during development, so the technical file is a by-product of the development process rather than a separate project
Connectivity protocol chosen based on familiarity (Wi-Fi, because the development team knows it) rather than product requirements — leading to battery life failures in field deployment where power budget analysis was never done
We perform connectivity protocol selection with explicit power budget analysis, range requirements review, and infrastructure dependency assessment — so the protocol choice is justified against the product's real operating conditions before any hardware is ordered
Firmware testing done manually by flashing devices and observing behaviour — no automated regression testing, so each firmware release requires hours of manual validation and regressions are discovered by customers
We build automated testing infrastructure — unit tests with Ceedling/Unity, HIL test frameworks where applicable, and static analysis — so firmware releases are validated against a regression suite and defects are caught before reaching hardware
Device cloud architecture built on generic web infrastructure — relational database with individual INSERT per telemetry reading, collapsing under the volume of even a few hundred devices sending sensor data at 1Hz
We build IoT backends on time-series databases (TimescaleDB, InfluxDB) with appropriate ingestion pipeline architecture — designed for the actual data volumes a device fleet generates, not adapted from a web application data model
TECH STACK
Every technology below is used in live embedded and IoT software deployments — from bare-metal C firmware on ARM Cortex-M targets through to React Native dashboards consuming real-time device telemetry.
C
C++
Python (scripting/test)
Rust (safety-critical)
Below are examples of embedded software and product engineering projects delivered by Automely. All client details are kept confidential.
HARDWARE SECTORS WE SERVE
We build firmware, IoT platforms, and product engineering stacks across the full range of hardware product categories — from consumer electronics to regulated medical devices.
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PRODUCT ENGINEERING QUESTIONS
What is embedded software?
Embedded software is software written to control a specific hardware device — as opposed to general-purpose software that runs on a computer or phone. The term 'embedded' refers to the fact that the software is embedded within the hardware product itself, typically stored in flash memory on a microcontroller or microprocessor, and runs when the device powers on. Embedded software controls the hardware's behaviour: reading sensor inputs, making decisions based on those inputs, controlling actuators and outputs, managing power states, and communicating with other devices or cloud services. Examples of devices running embedded software include: thermostats, medical monitors, industrial controllers, automotive ECUs, smart home devices, wearables, industrial robots, and consumer electronics.
Unlike application software, embedded software typically runs without a conventional operating system (or with a minimal real-time operating system), has strict memory and processing constraints, must meet deterministic timing requirements, and in many cases cannot be easily updated after deployment — making correctness at the point of release critical. Embedded software is predominantly written in C and C++, though Rust is growing in use for safety-critical applications.
What is product engineering?
Product engineering is the end-to-end process of designing, developing, and maintaining a technology product — covering the full software stack from conception through to production-grade deployment and ongoing iteration. In the context of hardware products, product engineering services typically cover all software layers: embedded firmware on the device, cloud backend processing device data, APIs connecting device and application, and the mobile or web application users interact with. In the context of software-only products, product engineering covers architecture, full-stack development, quality assurance, DevOps infrastructure, and ongoing product iteration. The distinction from project-based software development is continuity: product engineering implies ongoing ownership of the product's quality and evolution, not just delivery of a defined scope.
What regulations apply to medical device software?
Medical device software is subject to regulatory requirements in every major market. In the US, the FDA classifies Software as a Medical Device (SaMD) under the Federal Food, Drug, and Cosmetic Act — the classification (Class I, II, or III) determines the pathway (510(k), De Novo, or PMA) and the level of evidence required. In the EU, SaMD is regulated under the Medical Device Regulation (MDR 2017/745) and in vitro diagnostic software under IVDR 2017/746. The primary software-specific standard across all markets is IEC 62304 — the software lifecycle process standard for medical device software — which defines requirements for software development planning, requirements analysis, architecture, detailed design, unit implementation and testing, integration and integration testing, system testing, and software release. Risk management for software is governed by ISO 14971. Cybersecurity for connected devices is increasingly regulated: the FDA's 2023 cybersecurity guidance and the EU's Cyber Resilience Act both impose specific requirements on networked medical devices.
What connectivity protocol should I use for my IoT device?
Protocol selection for IoT devices depends on three constraints: range, power budget, and data rate required.
| Protocol | Range | Power | Data Rate | Best For |
|---|---|---|---|---|
| Bluetooth LE 5.x | <100m | Very low | Low–Medium | Wearables, smart home, medical |
| Wi-Fi (802.11) | <50m | Medium–High | High | Home/office devices, cameras, always-on |
| Thread / Matter | <30m mesh | Low | Low | Smart home mesh networks |
| LTE-M | Cellular | Low | Medium | Asset tracking, remote sensors |
| NB-IoT | Cellular | Very low | Very low | Deep coverage, low-data sensors |
| Zigbee | <30m mesh | Low | Low | Industrial sensors, building automation |
| LoRaWAN | >10km | Very low | Very low | Wide-area agriculture, utilities |
For consumer products in the home, Bluetooth LE for local control and Wi-Fi for cloud connectivity is the most common combination. For industrial or outdoor devices that need to operate independently of existing network infrastructure, LTE-M or NB-IoT with a SIM is typically the right choice. Thread and Matter are the emerging standards for smart home interoperability — relevant if compatibility with Apple Home, Google Home, and Amazon Alexa is a product requirement.
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