Software engineers have it good. Need to collaborate on a codebase? Push to GitHub. Want to reuse a library someone else built? Pull from a package registry. Looking for how a project is structured? Browse it publicly, fork it, build on it. The entire software world benefits from a shared culture of open collaboration, version control, and reusable components.

Hardware engineering doesn’t have that.

Today, system models, requirements documents, interface definitions, and design rationale live scattered across emails, SharePoint folders, and static PDFs. When a project ends, that knowledge largely disappears, siloed in someone’s hard drive. The next team starting a similar project has no way to build on what came before and most often starts again from scratch.

We think that needs to change. And we’re building Davinci to be the platform that changes it.

The Problem with “Hardware Knowledge”

The challenge of design is largely one of knowledge management. Software has a solid foundation of version control and public repositories. Decades of open-source tooling, package ecosystems, and shared codebases mean that a software engineer today inherits an enormous base of reusable knowledge and proven solutions to build upon. Like software, almost all complex hardware systems reuse or integrate existing technologies and subsystems.

Despite that, hardware engineering has no equivalent infrastructure. Model-Based Systems Engineering (MBSE) tools are among the closest solutions for capturing intent and architecture in digital models, but in practice they carry a steep learning curve and high licensing costs. They’re authoring tools, not knowledge platforms. CAD environments and PLMs address certain aspects of design knowledge, but there’s no equivalent of browsing a public repo, searching across projects, or pulling in a component someone else already validated. Existing tooling is simply too fragmented, each piece focused on a narrow slice of the picture. Digital models that connect intent, validation, and design specifications are the clear solution, but historically is specialized work gated behind specialty software and significant training investment. 

Making Digital Models Easy

Davinci was built to remove the barrier to digital engineering entirely. Our focus from the start has been to create a general-purpose knowledge management system for engineering, not just another modeling tool. Requirements, architectures, interfaces, trade studies, risk analyses, and design decisions all live together in a single structured environment. We’ve deliberately positioned Davinci between the worlds of PLM, MBSE, and even tools like Notion, creating an environment where everything is connected, searchable, and linkable. The ability to trace from a requirement to a reference document to an analysis script is what makes the difference between a drawing tool and an institutional memory.

Most importantly, we’ve rebuilt this process from the ground up to be much easier, from the UX to the agentic AI systems that automate the heavy lifting. Creating a digital model in Davinci is far faster and cheaper than before. On top of that, getting started is free. That combination of ease and cost is what makes a digital modeling ecosystem possible for the first time. 

Our Vision: An Open Hardware Ecosystem

We envision a world where digital engineering is the basis for all design efforts, not a speciality process. The natural extension of that is expanding hardware knowledge into a living model ecosystem, the same way GitHub became the home for software.

That means two things working together. First, open-source hardware projects that share everything: architecture, requirements, interfaces, trade studies, the works. Researchers, students, and open engineering communities can collaborate publicly, build on each other’s work, and participate in the kind of foundational knowledge-sharing that software has enjoyed for decades.

Second, commercial projects that participate on their own terms. A company building a proprietary subsystem doesn’t need to expose its IP to benefit from the ecosystem. It can publish a black-box representation of its product without revealing what’s inside. Other engineers can find it, understand how to integrate with it, and reference it in their own designs. The ecosystem grows without forcing anyone to give up what they’ve built.

Finally, tying all of this together is AI. From creating models to finding the right component, we’re building AI-native discovery into Davinci so that navigating the ecosystem is as natural as asking a question. As design agents become more capable, this kind of structured knowledge base becomes an increasingly powerful foundation for scaling collaboration and accelerating advancement.

What’s Coming

Over the next few months, we’re aiming to ship a focused set of features to make this vision real.

• Organizations are coming soon. Whether you’re a university lab, a research group, a startup, or a large engineering organization, you’ll have a home in Davinci with shared projects, team management, and a public presence. The team plan foundation we shipped in 4.2 is the first step; organizations are next.

• Search and discovery in our Explore page will let you see the broader Davinci ecosystem to find public projects, components, and models relevant to what you’re working on. This is where the platform starts to feel less like a tool and more like a community.

• Improved importing inside of projects will make it easier to link and reuse designs across projects. Reference someone else’s subsystem, pull in a validated interface definition, or fork a public model as the starting point for your own work — the same reusability that makes package managers so valuable in software.

For Researchers and Students

Unlike the enterprise tools that dominate this space, Davinci is free to get started with no limits on manual editing. Anyone can sign up today, create a project, and start building.

If you’re running something larger, like a university research program, a multi-semester capstone effort, or a lab with several collaborators, we want to talk. We’re actively developing reduced-cost plans for research institutions and academic programs. Reach out to us at contact@celedon.solutions and tell us what you’re working on and what you need.

To the Community

We’re building this for engineers across industry, government, and academia. But the right ecosystem doesn’t get built in a vacuum. We want to know what features matter most to you, what friction you hit today when trying to share or reuse engineering knowledge, and where you think a platform like this could have the most impact.

Reach out directly to anyone on the team or drop us a note through the site.

The foundation is here. The ecosystem is next.