Embedded that ships like software. Tested on real silicon, every commit.

Software teams solved slow feedback decades ago - embedded teams still pay for it in manual bench sessions, release candidates tested by hand, and regressions found by customers. needCode builds the infrastructure that closes that gap: hardware-in-the-loop test stands running firmware on real silicon, automated RF and protocol testing with evidence-grade capture, and CI/CD pipelines built for firmware. Regressions caught per commit, not per release. From an EU-based, ISO 9001-certified Qorvo partner.
needCode IoT

We work with Industry Leaders

The most expensive bug is the one that waits for a human to find it

In embedded, the feedback loop is where quality is decided. When testing means an engineer at a bench, feedback comes in days - so bugs are found late, when they're expensive; RF regressions slip through invisibly, because no unit test sees a degraded link budget; and releases become events that teams brace for instead of routine outputs of a pipeline. The standard excuse is that hardware can't be automated. It can - firmware running on real silicon, exercised automatically on every commit, with radio traffic captured as evidence - and the teams that build this infrastructure ship faster and safer, because those stopped being a trade-off.

needCode builds it as a discipline, not a bolt-on: hardware-in-the-loop environments where real hardware meets simulated conditions, wireless protocols verified under controlled RF propagation, and pipelines that treat firmware like the software it is. It's the methodology behind our own delivery - DevOps for engineering, under ISO 9001 - offered as a service.

Real silicon, not simulators

Automated test stands run your firmware on target hardware - because the bugs that matter live in the firmware-hardware boundary.

RF regressions, made visible

Protocol and radio behaviour tested under controlled conditions, with capture as evidence - including our own UWB protocol sniffer in the loop.

Per commit, not per release

CI/CD pipelines built for firmware - reproducible builds, automated gates, releases as routine.

What we build

Four layers of test infrastructure, each one turning a manual bottleneck into an automated gate.

Hardware-in-the-Loop Frameworks

Automated test stands where firmware runs on real silicon against simulated and controlled physical conditions - exercised on every commit, not when a bench engineer has time. The hard part isn't the rack; it's engineering flakiness out of tests that involve real radios, real timing, and real environmental noise, so a red build means a real bug.

RF & Protocol Test Automation

Automated verification of wireless behaviour - BLE, UWB, Zigbee, Matter, WiFi - under controlled RF propagation, with pass/fail rules running on live radio traffic and captures stored as evidence. Our own UWB Protocol Sniffer plugs into the bench through its REST API, giving pipelines an instrument the silicon vendors don't offer.

CI/CD Pipelines for Embedded

Build, test, and release pipelines adapted to firmware's realities - reproducible Docker and dev-container builds, hardware farms as pipeline stages, artefact management, and release automation that makes shipping boring. Generic DevOps tooling assumes the deploy target is a server; firmware needs the pipeline rebuilt around flashing, fleets of boards, and binary provenance.

Regression & Qualification Automation

Automated regression suites that keep yesterday's fixes fixed, plus qualification automation that compresses formal test campaigns - Bluetooth PTS runs that took weeks of manual clicking become an overnight job. This is the layer that de-risks the certification date; the certification outcome itself is owned by our Standards & Certification service.

Still testing releases by hand?

Book a discovery call with our CEO

Where this infrastructure pays off

Test automation isn't a project - it's the floor under every programme that has to ship repeatedly. Four places it earns its cost fastest.

SDK & Platform Programmes

An SDK is judged by whether the next release breaks the customer - so every commit needs the full battery on real hardware, across every supported board. This is the discipline behind long-running platform work at silicon scale.

Certification on the Critical Path

Products that arrive at certification pre-tested pass instead of iterating - pre-certification suites run continuously, so the formal campaign confirms rather than discovers. The fastest certification is the one with no surprises in it.

Automotive & Digital Key HIL

Digital key and secure-ranging programmes demand HIL benches that speak CAN, exercise multi-anchor UWB sessions, and prove ranging behaviour release after release - with the sniffer capturing the radio truth on every run.

RTLS & Positioning Validation

Positioning systems regress quietly - an anchor firmware update shifts accuracy and nobody notices until operations do. Automated accuracy and behaviour testing catches the drift while it's still a diff, not an incident.

Why teams bring us their testing

Forged at silicon scale

Our test culture comes from an 8-year Qorvo R&D partnership across 9 hardware-platform bring-ups - the environment where an SDK release faces every supported board, automatically, before it ships. We're not selling a theory; we're packaging how we already work.

We build our own instruments

When no vendor sells the tool, we build it - the UWB Protocol Sniffer exists because our own benches needed evidence-grade radio capture, and its REST/CI-CD interface was designed for exactly the pipelines this page describes.

Qualification, compressed

We automated Bluetooth PTS qualification from weeks of manual work to an overnight run - the kind of compression that moves a certification from the critical path to a checkbox.

Discipline you can audit

ISO 9001-certified processes and a DevOps-for-engineering methodology - reproducible builds, traceable results, documentation as a product - the posture a regulated or safety-conscious buyer expects to find behind a test report.

Four ways to bring needCode in

From an audit of what you have to a standing quality team. We match the engagement to where your delivery hurts.

01

Test Infrastructure Audit & Roadmap

  • Duration:
    2-4 weeks
  • Best for:
    Teams that know feedback is too slow but need a concrete plan - what to automate first, what it costs, what it returns
  • Deliverable:
    Audit of the current build/test/release path, prioritised automation roadmap, HIL architecture proposal, leadership readout

02

HIL & Pipeline Build

  • Duration: 
    Phased
  • Best for:
    Building the core infrastructure - HIL stands, hardware farm, CI/CD pipeline, reproducible builds - around your product and boards
  • Deliverable:
    A working per-commit pipeline running firmware on real hardware, with documentation and handover

03

RF, Regression & Qualification Automation

  • Duration: 
    Phased
  • Best for:
    Extending the pipeline upward - automated RF verification with capture evidence, regression suites, PTS and pre-certification automation
  • Deliverable:
    Automated protocol test suites, sniffer-backed RF gates, qualification runs compressed to overnight jobs

04

Embedded Quality Team

  • Duration: 
    Multi-year, retainer-based
  • Best for:
    Programmes that want testing owned continuously, inside their cadence, as the product and board matrix grow
  • Deliverable:
    An embedded team in your cadence - the model behind the 30-FTE Qorvo programme

What we ship on

We build on your stack where it exists and bring our own instruments where it doesn't.

HIL & instruments

Custom HIL rigs
UWB Protocol Sniffer (in-house)
controlled RF environments
target-board farms
power & environmental instrumentation

Protocols under test

UWB
BLE
Zigbee
Matter
WiFi
multi-protocol coexistence

Pipelines

GitLab CI
GitHub Actions
Jenkins
Docker / dev-container reproducible builds

Test layers

protocol & RF
firmware-hardware interaction (HIL)
system performance, scalability, reliability
environmental (temperature, vibration, interference)
Unit & integration (embedded components)

Qualification

Automated Bluetooth PTS
pre-certification suites
FiRa / CCC test readiness

Reporting

Schema-stable JSON
dashboards
pass/fail gates
capture archives as evidence

Case studies

needCode doesn't publish a standalone test-automation case study. What we can show is where the discipline comes from - and the instrument it produced.

Qorvo: RF Leadership

Context: Rapid scaling for new chipset bring-up.
  • Scale: Grew from <10 to 30 FTEs.
  • Output: Supported bring-up of 9 new hardware platforms (SDKs, Drivers, Stacks).
  • Retention: Zero-churn core team retained for 5+ years.
Dedicated Development Center for RF Solutions
Bluetooth Mesh Smart Lighting Control System

Smart Lighting: Core R&D Extension

Context: Client needed deep, specialized expertise to pivot from proprietary tech to a new global standard.
  • Service: Deployed a dedicated squad of embedded engineers to function as the client's core R&D team.
  • Output: Co-authored official Bluetooth SIG protocols and delivered the world’s first certified BLE Mesh stack.
  • Value: Enabled the client to secure Series A funding and defined the industry standard for smart buildings.

Creative Werks: Innovation rescue

Context: Hardware obsolescence threatened production shutdown.
  • Action: Full-stack takeover (PCB redesign + Firmware + Mobile App).
  • ROI: 1230% ($1.6M value generated).
  • Speed: Payback period of 2-3 months.
NeedCode-case study - IoT Solution for Boat Lift Modernization - cover2s
needcode-powerpolen-case-study-cover2s

PowerPollen: AgTech automation

Context: Lack of internal expertise stalled a critical automation project.
  • Action: Re-architected system using unified MCU and ISOBUS standards.
  • ROI: 13.8x ($2.9M value generated).
  • Impact: Enabled $1.9M increase in harvester value.

Strategic Partnership

needCode is an official business partner of Qorvo, bringing over 8 years of proven expertise and trusted service to the technology sector.
qorvo-logo-banner
UWB-Alliance-logo-banner

Members of the UWB Alliance

In 2025 we became a member of the UWB Alliance. This strategic step reinforces our commitment to pioneering Ultra-Wideband (UWB) technology.

Proudly Certified for Excellence and Security

needCode is officially certified for:
ISO 9001:2015 – Quality Management
ISO/IEC 27001:2022 – Information Security
ISO certifications reflect our focus on delivering reliable IoT solutions, smart product development, and secure technology services.
ISO 9001_2015ISO - IEC 27001_2022

Testimonials

“I think the key takeaway from needCode is their ability to adapt and understand the customer's requirements. That took away probably a large portion of what could have been a lot of development time and expense for both companies.”
Bob Folkestad
Bob Folkestad
President at Creative Werks
“One aspect that truly sets needCode apart is its profound expertise in firmware development. Their proficiency in various programming languages, embedded systems and hardware architecture is truly impressive. When faced with difficult problems, their strong problem-solving skills and analytical mindset shine through, allowing them to overcome obstacles with remarkable ease.”
avatar Semeh Sarhan
Semeh Sarhan
CEO at Xtrava
“I worked with needCode while leading the NWTN-Berlin team in 2018. A big chunk for our FW development has been outsourced to them and they had proven to iterate very quickly, following specs and deliver on time. It was great working with them. I recommend working with needCode’s team on any Embedded SW development.”
avatar Marco Salvioli Mariani
Marco Salvioli Mariani
CTO at NWTN Berlin GmbH
“needCode Team proved to be one of the best engineers I have ever met. The part I like the most about the team is the more difficult an obstacle seems to be, the more motivated they were to find a solution and a way forward.”
A Testimonial picture
Szymon Słupik
CTO at Silvair
“needCode is an outstanding partner. Their quick follow-up, scalability, and extensive professional network set them apart. Their expertise in wireless technologies has been valuable, supporting us from low-level drivers to architecture discussions.”
avatar Tim Allemeersch
Tim Allemeersch
Director at Qorvo, Inc.
“needCode did a great job improving the firmware of the Vai Kai connected toys and developing new features, surpassing our expectations multiple times. I would definitely recommend hiring Bartek and needCode for the embedded software projects!”
avatar Matas Petrikas
Matas Petrikas
CEO & Co-founder
at Vai Kai UG

Insights

FAQ

Hardware-in-the-loop testing runs firmware on real target hardware while the surrounding environment - signals, conditions, peer devices - is simulated or controlled, so firmware-hardware interactions can be tested automatically in realistic scenarios. It's the layer that catches the bugs living at the firmware-hardware boundary, which pure software tests can't see. needCode designs and builds HIL frameworks that run on every commit, turning manual bench sessions into repeatable automation.

Yes - the difference is that the pipeline must be rebuilt around firmware's realities: flashing real boards as a pipeline stage, hardware farms instead of cloud runners, reproducible Docker or dev-container builds, and binary artefact provenance. Once that's in place, firmware ships the way software does - per commit, through automated gates, with releases as routine rather than events. needCode builds these pipelines as a service, using the same methodology behind its own delivery.

Wireless behaviour is verified under controlled RF conditions - link performance, protocol correctness, and coexistence for BLE, UWB, Zigbee, Matter, and WiFi - with pass/fail rules executing against live radio traffic and captures archived as evidence. For UWB, needCode's own protocol sniffer plugs into the bench through a REST API, giving the pipeline an instrument no silicon vendor offers. RF regressions are invisible to unit tests; this is the layer that makes them visible.

Run manually, a full Bluetooth PTS campaign typically consumes weeks of engineer time clicking through test cases; automated, needCode runs it as an overnight job. That compression moves qualification off the critical path and lets pre-certification testing run continuously during development instead of once at the end. The certification outcome itself - BT SIG, FiRa, CCC - is handled by needCode's Standards & Certification service, which this automation feeds.

Flakiness is engineered out, not tolerated: deterministic test design, controlled RF environments, instrumented retries that distinguish environmental noise from real failures, and quarantine mechanisms so an unstable test can't erode trust in the pipeline. A hardware test suite is only useful if a red build means a real bug. This is the hardest part of HIL work - and the reason generic CI consultants struggle with embedded.

No - automation takes over the repetitive, regression-prone, per-commit work, which frees human testing for what it's actually good at: exploratory testing, usability, and the judgment calls no script makes. The goal is that no human ever re-verifies yesterday's behaviour by hand. In practice, teams end up doing more meaningful manual testing, not less, because the routine burden is gone.

Yes - needCode builds on what exists: pipelines integrate with common CI platforms, HIL stands incorporate your current instruments and boards, and results flow into your reporting in schema-stable formats. Where a capability is missing - evidence-grade UWB capture, controlled RF, board farms - we add it. An audit engagement maps the current state first, so the roadmap extends your investment instead of replacing it.

Directly: products that arrive at certification pre-tested pass instead of iterating, because pre-certification suites have been running continuously against the spec throughout development. This page's automation is the infrastructure; the certification outcome - Bluetooth SIG, FiRa, CCC conformity - is owned by needCode's Standards & Certification service. Together they turn the certification date from a risk into a checkpoint.

A rack (or lab) of target boards - ideally every hardware variant you support - wired for automated flashing, power control, and instrumentation, exposed to the CI system as a pipeline stage. Every commit builds reproducibly, flashes the farm, runs the suites, and gates the merge on real-silicon results. needCode designs the farm around your actual board matrix and scales it as the matrix grows.

Yes - from an audit of the current build/test/release path, through HIL frameworks and hardware farms, RF and protocol automation with capture evidence, to CI/CD pipelines and qualification automation, with documentation and handover or a standing embedded quality team. The methodology is the one needCode runs internally under ISO 9001, forged in an 8-year silicon-scale Qorvo programme. One team owns the infrastructure and the discipline.

Let's work on your next project together

Book a demo and discovery call with our CEO
to get a look at:
Strategic Expertise
End-to-End Solutions
Advanced Technology
Custom Hardware Devices
Bartek Kling
Bartek Kling / CEO
© 2026 needCode. All rights reserved.

Manufacturing

Modern manufacturing machines are typically equipped with IoT sensors that capture performance data. AIoT technology analyzes this sensor data, and based on vibration patterns, the AI predicts the machine's behavior and recommends actions to maintain optimal performance. This approach is highly effective for predictive maintenance, promoting safer working environments, continuous operation, longer equipment lifespan, and less downtime. Additionally, AIoT enhances quality control on production lines.

For example, Sentinel, a monitoring system used in pharmaceutical production by IMA Pharma, employs AI to evaluate sensor data along the production line. The AI detects and improves underperforming components, ensuring efficient machine operation and maintaining high standards in drug manufacturing.

Logistics & supply chain

IoT devices - from fleet vehicles and autonomous warehouse robots to scanners and beacons - generate large amounts of data in this industry. When combined with AI, this data can be leveraged for tracking, analytics, predictive maintenance, autonomous driving, and more, offering greater visibility into logistics operations and enhancing vendor partnerships.

Example: Amazon employs over 750,000 autonomous mobile robots to assist warehouse staff with heavy lifting, delivery, and package handling tasks. Other examples include AI-powered IoT devices such as cameras, RFID sensors, and beacons that help monitor goods' movement and track products within warehouses and during transportation. AI algorithms can also estimate arrival times and forecast delays by analyzing traffic conditions.

Retail

IoT sensors monitor movement and customer flow within a building, while AI algorithms analyze this data to offer insights into traffic patterns and product preferences. This information enhances understanding of customer behavior, helps prevent stockouts, and improves customer analytics to drive sales. Furthermore, AIoT enables retailers to deliver personalized shopping experiences by leveraging geographical data and individual shopping preferences.

For instance, IoT sensors track movement and customer flow, and AI algorithms process this information to reveal insights into traffic patterns and product preferences. This ultimately leads to better customer understanding, stockout prevention, and enhanced sales analytics.

Agriculture

Recent research by Continental reveals that over 27% of surveyed farmers utilize drones for aerial land analysis. These devices capture images of crops as they are and transmit them to a dashboard for further assessment. However, AI can enhance this process even further.

For example, AIoT-powered drones can photograph crops at various growth stages, assess plant health, detect diseases, and recommend optimal harvesting strategies to maximize yield. Additionally, these drones can be employed for targeted crop treatments, irrigation monitoring and management, soil health analysis, and more.

Smart Cities

Smart cities represent another domain where AIoT applications can enhance citizens' well-being, facilitate urban infrastructure planning, and guide future city development. In addition to traffic management, IoT devices equipped with AI can monitor energy consumption patterns, forecast demand fluctuations, and dynamically optimize energy distribution. AI-powered surveillance cameras and sensors can identify suspicious activities, monitor crowd density, and alert authorities to potential security threats in real-time, improving public safety and security.

For example, an AIoT solution has been implemented in Barcelona to manage water and energy sustainably. The city has installed IoT sensors across its water supply system to gather water pressure, flow rate, and quality data. AI algorithms analyze this information to identify leaks and optimize water usage. Similarly, smart grids have been introduced to leverage AI to predict demand and distribute energy efficiently, minimizing waste and emissions. As a result, these initiatives have enabled the city to reduce water waste by 25%, increase renewable energy usage by 17%, and lower greenhouse gas emissions by 19%.

Healthcare

Integrating AI and IoT in healthcare enables hospitals to deliver remote patient care more efficiently while reducing the burden on facilities. Additionally, AI can be used in clinical trials to preprocess data collected from sensors across extensive target and control groups.

For example, intelligent wearable technologies enable doctors to monitor patients remotely. In real-time, sensors collect vital signs such as heart rate, blood pressure, and glucose levels. AI algorithms then analyze this data, assisting doctors in detecting issues early, developing personalized treatment plans, and enhancing patient outcomes.

Smart Homes

The smart home ecosystem encompasses smart thermostats, locks, security cameras, energy management systems, heating, lighting, and entertainment systems. AI algorithms analyze data from these devices to deliver context-specific recommendations tailored to each user. This enables homeowners to use utilities more efficiently, create a personalized living space, and achieve sustainability goals.

For example, LifeSmart offers a comprehensive suite of AI-powered IoT tools for smart homes, connecting new and existing intelligent appliances and allowing customers to manage them via their smartphones. Additionally, they provide an AI builder framework for deploying AI on smart devices, edge gateways, and the cloud, enabling AI algorithms to process data and user behavior autonomously.

Maintenance (Post-Release Support)

When your product is successfully launched and available on the market we provide ongoing support and maintenance services to ensure your product remains competitive and reliable. This includes prompt resolution of any reported issues through bug fixes and updates.

We continuously enhance product features based on user feedback and market insights, optimizing performance and user experience.

Our team monitors product performance metrics to identify areas for improvement and proactively addresses potential issues. This phase aims to sustain product competitiveness, ensure customer satisfaction, and support long-term success in the market.

Commercialization (From MVP to Product

Our software team focuses on completing the full product feature range, enhancing the user interface and experience, and handling all corner cases. We prepare product software across the whole lifecycle by providing all necessary procedures, such as manufacturing support and firmware upgrade.

We also finalize the product's hardware design to ensure robustness, scalability and cost-effectiveness.

This includes rigorous testing procedures to validate product performance, reliability, and security. We manage all necessary certifications and regulatory compliance requirements to ensure the product meets industry standards and legal obligations.

By the end of this phase, your product is fully prepared for mass production and commercial deployment, with all documentation and certifications in place.

Prototyping (From POC to MVP)

Our development team focuses on implementing core product features and use cases to create a functional Minimum Viable Product (MVP). We advance to refining the hardware design, moving from initial concepts to detailed PCB design allowing us to assemble first prototypes. Updated documentation from the Design phase ensures alignment with current project status. A basic test framework is established to conduct preliminary validation tests.

This prepares the product for real-world demonstrations to stakeholders, customers, and potential investors.

This phase is critical for validating market readiness and functionality before proceeding to full-scale production.

Design (From Idea to POC)

We meticulously select the optimal technology stack and hardware components based on your smart product idea with detailed use cases and feature requirements (Market Requirements Document / Business Requirements Document). Our team conducts thorough assessments of costs, performance metrics, power consumption, and resource requirements.

Deliverables include a comprehensive Product Requirements Document (PRD), detailed Software Architecture plans, an Initial Test Plan outlining validation strategies, Regulatory Compliance Analysis to ensure adherence to relevant standards, and a Proof of Concept (POC) prototype implemented on breakout boards.

This phase aims to validate the technical feasibility of your concept and establish a solid foundation for further development.

If you lack a validated idea and MRD/BRD, consider utilizing our IoT Strategic Roadmap service to gain insights into target markets, user needs, and desired functionality. Having a structured plan in the form of an IoT Strategic Roadmap before development begins is crucial to mitigate complications in subsequent product development phases.