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Outsourced engineering now runs with AI in the loop. In Deloitte’s 2024 Global Outsourcing Survey of 500+ executives, 83% said they use AI as part of their outsourced services.
For a medical device company, that changes what a vendor pitch has to prove. Fast delivery helps a regulated product only when every AI-assisted change stays reviewed, traceable, and ready for an IEC 62304 audit. Proposals tend to look alike at first glance, so the deciding test is the evidence behind each one.
This guide lists the evidence to request from every vendor, the proposal red flags worth questioning, and a 4-step way to run your evaluation. It also profiles top medical device software development companies, each with medical device work you can check against your own plans.
Vendor websites and pitch decks describe capabilities in similar terms. The difference shows up in documents a team can produce only after real medical device work. Request these 7 items from every candidate:
| Vendor Claim | Evidence to Request | What It Tells You |
|---|---|---|
| “We build medical device software” | 2 to 3 device case studies with device class, target market, and the team’s scope | Whether their work matches your device’s risk class and market |
| “We follow IEC 62304” | A redacted software development plan and a traceability matrix from a past project | Whether lifecycle records exist at the depth your submission needs |
| “We manage risk” | An ISO 14971 risk file excerpt with software hazards and controls | How the team links hazards to design and tests |
| “We handle cybersecurity” | A threat model and an SBOM from a past connected device | Whether they can meet FDA expectations for cyber devices |
| “We use AI to deliver faster” | Their written policy for AI-assisted code, with review and traceability rules | Whether speed comes with the controls an auditor will ask about |
| “Our team is senior” | CVs of the engineers assigned to your project, with medical device roles named | Who builds your product day to day |
| “We support you after launch” | A sample change impact assessment and their post-market update process | How they ship patches and keep compliance intact |
A proposal shows how a team thinks before any code exists. These 5 patterns deserve a direct question:
A proposal that prices regulatory documentation as one lump at the end suggests the team writes it after the code. Ask how documentation moves through each sprint and who reviews it. A strong answer names the documents for each stage, such as requirements, risk files, and test records, and shows how they update with the build.
Effort for IEC 62304 Class A and Class C software differs widely, so an estimate without a stated class rests on a guess. Ask which class the team assumed and why. A strong answer ties the class to your intended use and explains how the estimate changes if the class moves up.
Open-source libraries and SDKs count as SOUP under IEC 62304, and each one needs requirements, a risk review, and monitoring. Ask how the team selects, documents, and tracks these components.
Faster delivery through AI tools helps only when every generated change goes through the same review and traceability as human-written code. Ask who approves AI-assisted changes and how the record shows it. A strong answer names a senior reviewer for each change and keeps AI use visible in the change history.
Titles such as senior developer or QA engineer say little about medical device experience. Ask for the names, CVs, and past device projects of the people assigned to your work. An answer should commit a named core team and explain how the same people stay on a multi-year product.
The table below puts the basic evidence for each company side by side: years in business, client rating, the standards they name, device work on record, and team and rate.
Use the table to narrow the field to vendors whose standards and past work match your device, then read the profiles for the starting point, terms, and proof each team brings. Your evidence requests then go only to the teams that already fit your product.
| Company | In Business | Clutch Rating | Regulatory Standards Named | Device Work on Record | Team and Rate |
|---|---|---|---|---|---|
| Relevant Software | 13+ years | 4.9 (32 reviews) | ISO 27001, HIPAA, GDPR | Össur scanning apps, AstraZeneca AI analytics | 92% senior engineers, $50 to $99/hr |
| Lemberg Solutions | 15+ years | 4.8 (27 reviews) | ISO 13485:2016, ISO 9001:2015, ISO 27001:2022, IEC 62304, MDR | Caltech mouthguard prototype, Carepath cough-monitoring platform | 200+ engineers, $50 to $99/hr |
| Vention | 20+ years | 4.9 (103 reviews) | ISO 27001, IEC 62304 testing, FDA Class I and II | Medical device and SaMD service line, Healthera prescriptions app | 3,000+ engineers, $50 to $99/hr |
| Velvetech | 22+ years | 5.0 (22 reviews) | IEC 62304, ISO 14971, HIPAA | Smart glucometer embedded UI | 250+ specialists, $50 to $99/hr |
| Topflight Apps | 10+ years | 4.9 (43 reviews) | IEC 62304, HIPAA | Joovv light therapy device app, AllHeartz monitoring app | About 40 people, $100 to $149/hr |
| Arkenea | 15+ years | 4.9 (14 reviews) | IEC 62304, ISO 14971, FDA, HIPAA | Medical device service line, 19 healthcare projects | 50+ staff, $50 to $99/hr |
Relevant Software belongs on the list of top medical device software development companies because their data, AI, and IoT specialists share one delivery team across wearables, IoMT devices, and the AI layer of a medical product.
Since 2013, they have delivered 200+ projects, hold a 4.9 rating on Clutch, and keep 96% employee retention, so the same people stay with a device through submission and later updates. Their AI-assisted delivery pairs AI tools with senior review and cuts delivery cycles by up to 50% and bugs by up to 20%.
Lemberg Solutions has built embedded systems for 15+ years and lists 10 healthcare projects in their portfolio. Their device work spans HMI, SaMD and SiMD, hardware prototyping, and PCB design, so electronics and software move forward on one plan.
The ISO 13485:2016 certification they obtained in 2023 covers medical device software delivery, and the team reports 94% client satisfaction. Partnerships with NXP, Microchip, and STMicroelectronics support their chip-level work.
Vention, known as iTechArt until 2023, has delivered 200+ healthtech projects over 20+ years in business, with 100+ healthcare experts on staff. Their medical device practice covers medical device software and SaMD, with experience in FDA Class I and II products.
A client base of 500+ companies, including 20+ that went on to IPO, gives the team long experience with products that grow fast.
Since 2004, Velvetech has completed 1,000+ projects for 400+ clients, and 150+ of those projects serve healthcare. Their IoMT practice builds software components that qualify as SaMD and links connected devices to the platforms care teams use. A Microsoft partnership supports the cloud side of that work.
Topflight Apps has built healthcare apps since 2016 for clients such as Stanford Medicine, Merck, and Medable. For Joovv, the team built the companion app for light therapy devices under IEC 62304 across 2,100 hours of work. Their AI work for GaleAI helped recover $1.14M in lost revenue.
Arkenea has worked only in healthcare since 2011, starting with a core team of 6, and lists 19 healthcare projects in their case studies. Their medical device service covers embedded software, SaMD, companion apps, V&V documentation, regulatory submission support, and post-market work. That scope lets one team carry a product from first build through updates after release.
A structured process keeps the choice on evidence. Each step narrows the field. Here are 4 steps that take you from a long list to a signed contract:
Choosing a medical device software partner is a regulatory decision as much as a technical one. The team you hire produces the records your submission depends on, and they stay with the product through every update after launch.
This week, you can send one brief and one evidence request to the top medical device software development companies on your list. The answers quickly show which teams have done this work before, and the discovery phase confirms it before you commit to the full build.
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