Building hardware is hard. Not just technically hard, but organizationally hard. You're juggling BOMs, vendor quotes, certification requirements, firmware revisions, and design documents, often before you've closed your seed round or hired your second engineer.
Software teams have had the infrastructure layer handled for years: version control, CI/CD, issue tracking, deployment pipelines. Hardware teams are still managing the equivalent workflow in Google Sheets, Slack threads, and email attachments. The gap is not subtle.
The tools that exist to manage this complexity were built for a different world.
Your Slack History Is Not a BOM
The symptoms show up before you name them.
A vendor quote comes back wrong because procurement had an older revision of your BOM. A firmware engineer makes a change that affects the mechanical enclosure, and the mechanical engineer finds out two weeks later at design review. Your CM is building from a PDF you sent in January. You patch it with a Slack message. A new engineer joins and spends their first two weeks reverse-engineering decisions that were made six months ago and never written down anywhere.
None of this requires negligence. Your team is working hard. The problem is that the current state of your product is distributed across inboxes, shared drives, and conversation threads with no authoritative source. When someone needs to know what the design actually says right now, the answer is a series of conversations, not a lookup.
That compounds as you add people. Every new hire inherits the ambient confusion of whoever came before them. Onboarding takes three times longer than it should because product knowledge isn't in a system: it's in a person. When that person leaves, the knowledge leaves with them.
The invisible cost isn't the mistakes. It's the engineer hours spent on meta-work: finding the right file version, confirming the current state, re-explaining context that should have been written down once and referenced forever.
Two Engineers on the Same BOM Is the Threshold
The most common answer hardware founders give when asked why they haven't set up proper PLM: "We're too early."
It sounds reasonable. You have a prototype, maybe two engineers, and a list of real product problems that dwarfs everything else. Adding process overhead feels like a tax on speed.
But the cost of delayed structure isn't visible until you're already paying it. The tipping point is usually one of three things: you hire your second or third engineer and realize no one knows the current state of the BOM; you approach a design freeze and discover three versions of the same assembly file on different laptops; or you start talking to a CM and can't produce a clean, current bill of materials.
By that point, you're not just setting up a system. You're untangling six months of undocumented decisions before you can even start.
There's also a downstream cost that founders underestimate. Early on, a bad PCB spin might cost a few thousand dollars: painful, but survivable. The calculus changes once you're ordering at volume, where a missed revision gets multiplied across every unit. And for tooling mistakes, the numbers are different from the start; a mold correction can run tens of thousands before you've shipped anything.
The cost that actually kills timelines is often neither. It's the weeks lost waiting on a re-spin or a re-order while a customer is waiting on delivery. Customers move on. They get frustrated. Some leave reviews. A process gap that looked like a $3,000 mistake at the BOM level can cost far more in relationships and schedule by the time it's resolved.
The other thing worth naming: investors and acquirers look at your engineering records. A due diligence process that turns up six versions of the same BOM, no change history, and no clear owner for critical design decisions is a red flag. Not a fatal one, but the kind that costs time and credibility at the worst possible moment.
Two engineers touching the same BOM is the threshold. If you're there, you're not too early.
The Tools You're Reaching For Instead
Before PLM, most hardware teams reach for what they already know.
Google Sheets works until someone makes a change and doesn't tell anyone. Then you have two versions. Then someone copies the wrong one into a quote request. Sheets has no concept of revision history, no audit trail, and no way to link a BOM line item to the requirement it's supposed to satisfy. The only person who knows which tab is current is the person who last touched it.
Notion or Confluence gives you a place to write things down. Documentation is useful. But a wiki is a snapshot of what someone thought was true when they wrote it, not the current state of the design. It doesn't track what changed, who approved it, or whether that approval is still valid six weeks later.
GitHub tracks code well. Some teams try to track hardware artifacts there too. For firmware, that makes sense. For MCAD files, production BOMs, and change orders, the workflow breaks fast. Git wasn't designed for binary files, part numbers, or the approval chains a manufactured product requires. A pull request is not an ECO. The diff view that makes code review useful is meaningless on a SolidWorks assembly or a CSV export of a 300-line BOM.
A shared folder with organized subfolders feels like a system. It is not a system. It's a filing cabinet with no index, no change history, and no way to know which file is the one that was actually released to production.
The pattern across all of them: they work at the beginning, then quietly accumulate debt. The information is technically in the system. It's spread across 40 documents, a Slack history, and three people's memories. That's not a data management problem; it's an organizational liability.
The Problem with Enterprise PLM
Traditional PLM software like Windchill, Teamcenter, or Arena were designed for teams of hundreds. The pricing reflects that. So does the onboarding process: expect a sales cycle, a demo, a proof-of-concept phase, and a multi-week implementation project before a single engineer can log in and do anything useful.
A 4-person hardware startup does not need a tool built for Boeing. They need something that works on day one, does not require a consultant to configure, and grows with the team.
The gap in the market is real. Enterprise PLM is overkill and the wrong shape. Ad-hoc spreadsheets and wikis are the wrong foundation. For most early-stage hardware teams, neither option fits, so they pick the one that costs less upfront and pay the price later.
What We Are Building Differently
After talking with hardware founders, four gaps keep coming up. Here is how oroForge addresses each one.
The 10% you actually use
Enterprise PLM carries decades of accumulated features, integrations, and configuration options. Most small teams use maybe 10% of those features and spend the rest of their time working around the other 90%.
oroForge is built around what hardware teams actually need: requirements, BOM, revision history, and vendor management. No configuration consulting. No feature bloat. If you need it, it's there. If you don't, it's not in your way. The goal was a tool that a founder could set up in an afternoon and an engineer could understand without training.
From sign-up to working in minutes
The standard PLM onboarding process involves a sales team, a demo cycle, a scoping call, a kickoff meeting, and a 6-week implementation. By the time you're live, your product has already changed.
oroForge is self-serve. Sign up, set up your project, and start working. No sales call required. No implementation partner. No wait. For an early-stage team, the ability to start on a Tuesday without scheduling anything is not a nice-to-have; it's the difference between using a tool and not using one.
A full history, not just the latest file
Git changed how software teams track changes. Hardware teams deserve the same: a full, permanent history of every requirement, BOM line item, and design decision.
Not just the current state, but the complete record. Who changed what, when, and why. That audit trail matters for certifications, post-mortems, and onboarding engineers who join mid-project. If a question comes up about why a component was swapped or when a spec was revised, the answer is in the system, not in someone's memory.
Built with AI in mind
Most PLM tools are passive repositories. You put data in, you get data out. The system does not help you think.
Hardware product development involves a lot of repetitive, structured work: generating documentation, checking compliance requirements, drafting RFQs, flagging downstream impacts of a design change. These are tasks engineers would happily delegate if they could.
We are building oroForge with that future in mind. PLM has always been dumb storage. We want to build something that gradually takes on the boring engineering operations work, so your team can focus on the parts that actually require an engineer.
Try It Today
oroForge is live. If you're working on a hardware product and tired of spreadsheets, Confluence wikis, and $20,000/year PLM systems, you can sign up and start building today. No sales call required. See oroForge pricing →
