The Open Source Gamble: Why Voxel51 Gave Away Their Core Technology to Win Enterprise Customers

Building enterprise software typically means keeping your intellectual property closely guarded. But in August 2020, Voxel51 made a counterintuitive bet: they released their core machine learning infrastructure as open source. In a recent episode of Category Visionaries, Jason Corso revealed how this decision transformed their business.

Breaking with Traditional SaaS

After pivoting from consulting, Voxel51 faced a crucial decision about their go-to-market strategy. “When we initially got started, we were in the full SaaS mindset,” Jason explains. “We’ll have some cloud based services. You send us your data and we will provide the insights and send it back to you.”

But early market feedback revealed a problem: enterprise customers weren’t ready to trust a startup with their sensitive data. Instead of fighting this reality, they embraced it.

The Open Source Strategy

“We ultimately decided to go with an open source, go to market strategy,” Jason shares. “We did this for a few reasons. One reason was we really believe in having a kind of like an educational impact on the best practices in the unstructured AI space.”

Their approach was generous but strategic: “We give away the full machine learning stack, the software, as long as it is one user, one machine, local data.” This meant developers could use the full power of their tools for free, but enterprise features like multi-user capabilities and security would require a commercial license.

Slow Growth to Breakthrough

The initial results were modest. “In the first months, we had like 20 weekly active users was like a big number for us,” Jason recalls. But rather than pivoting away from open source, they doubled down on community engagement.

They set up a Slack community and maintained active presence on GitHub, constantly interacting with users. The breakthrough came through strategic integrations, particularly becoming “the preferred mechanism for accessing a dataset called Google open images.”

The Enterprise Conversion Path

The path to enterprise sales emerged organically through community engagement. “About a year later when we inbounded a question from someone in the community… they kind of gave us the how to establish our go to market,” Jason explains.

Their commercial offering evolved to add “the multi user capabilities, the enterprise security support, the system versioning like dataset versioning – all the things that you may want to do in a company, you don’t really necessarily need to do as an individual who’s trying it out.”

Building Trust Through Authenticity

Throughout this journey, Voxel51 maintained a commitment to authenticity. “We never talk about vaporware. We never promise things in our customer discussions,” Jason emphasizes. “We were very careful to build that trust in that relationship over time.”

This extended to their marketing approach. Instead of flashy landing pages, “Nowadays if you look at our website, it’s a very technical website, many links to the documentation directly. There aren’t many like these ‘workflow x’ or ‘workflow y’ landing pages.”

The Community Feedback Loop

For technical founders considering open source, Jason emphasizes its value beyond just distribution: “I just think it’s so important to understand how users of your technology use the technology, which may not be the way you think you expected them to use the technology. It is so valuable and you’re going to get that feedback very rapidly if you engage the open source community.”

This feedback loop has become central to their growth. They actively monitor community engagement to guide their outbound sales efforts, using it as “a window into how to actuate our account execs when they’re going outbound to see who to talk to.”

The lesson for founders? Sometimes giving away your core technology isn’t just about distribution – it’s about building the trust and understanding needed to win enterprise customers. As Jason puts it, “I think that if you can do open source as a go to market strategy in this, anything related to the AI space, I think it will pay its dividends, maybe not immediately, but in the long term.”