The Founder Who Turned a Weekend Prototype into a $40M Series A in 18 Months

The hackathon prototype that becomes a real company is a startup mythology — told often, believed rarely. Daniel Reyes lived it. And he is the first to tell you that the story everyone wants to hear is not quite the story that happened.

The $40M Series A is real. The 18 months is real. What isn't real is the idea that it was inevitable, or that any single decision made it happen.

The Weekend That Started It

Reyes had been a product manager at a mid-sized HR software company for three years when he attended a hackathon focused on workforce analytics. He wasn't there to build a company. He was there to keep his technical skills from atrophying and because one of his former colleagues had organized it and asked him to come.

The problem he chose to work on was one he had been thinking about for months: the gap between how companies described their organizational structure in official org charts and how work actually flowed between people and teams. He had watched executives make reorganization decisions based on charts that bore almost no relationship to the actual communication and dependency patterns in the organization. The result was restructurings that broke things that were working and didn't fix things that weren't.

Over 48 hours, Reyes and two engineers he met at the hackathon built a prototype: a tool that ingested communication metadata — calendar invites, email headers, messaging platform activity, all anonymized — and generated a map of actual organizational relationships. Not the reported hierarchy, but the emergent one. Who was actually coordinating with whom. Where the bottlenecks were. Which teams were siloed and which were deeply integrated despite being nominally separate.

The prototype won the hackathon. More importantly, the three VPs from a large financial services company who were attending as judges asked for a demo within a week. Reyes built the demo. They asked for a pilot. He built the pilot. Eight weeks after the hackathon, his prototype was running on anonymized data from a 4,000-person organization, and the results were, in his words, "startling to everyone, including me."

The Gap Between Prototype and Product

The gap between a working prototype and a sellable product is one of the most consistently underestimated distances in startups. Reyes describes the first six months after the hackathon as the hardest period of the entire 18-month journey — harder than the fundraise, harder than the hiring, harder than the moments of genuine uncertainty about whether the company would survive.

"The prototype worked on the specific data set we had. It didn't work on three other data sets we tried. The privacy framework we had sketched in 48 hours was not something I'd let near a real customer's data. The output was interpretable to engineers who had built it and completely opaque to the HR leaders who were supposed to act on it. We had a working demo of a concept. We had zero product."

The three engineers from the hackathon became the founding team. Reyes convinced two of them to join full-time by offering equity he wasn't certain he had the legal framework to grant — one of the first of many things that required a lawyer to retroactively fix. The third joined as an advisor. They worked out of Reyes's apartment for five months, with no external funding, living off their savings and a small amount of consulting revenue from the financial services pilot, which had agreed to pay a nominal fee in exchange for using their infrastructure as a development environment.

The product that emerged from those five months was genuinely different from the prototype. The privacy model was rebuilt from first principles — no individual-level data was ever stored or surfaced, only aggregated relationship patterns above team-level thresholds. The output visualization was redesigned four times based on feedback from HR leaders who were, consistently, less interested in comprehensive network maps and more interested in a specific set of diagnostic questions: where are decisions slowing down, where are teams working in isolation that shouldn't be, which leaders have organizational influence that their title doesn't reflect. The product stopped trying to answer everything and started answering those questions, well.

The Fundraise That Almost Wasn't

Reyes started the formal fundraising process at month nine, with a product that worked, a paying pilot customer, and a waitlist of eight other companies who wanted access. He had a network of advisors who had suggested he was ready. He had a deck that, by his own assessment, was good.

He received 47 rejections over the following three months. The objections varied in their specifics but clustered around two concerns: the privacy risk was too high for institutional investors to take on at the seed stage, and the buyer in enterprise organizations — HR leadership — was historically difficult to sell to and slow to make decisions. Both objections were reasonable. Neither was disqualifying. But together, they were enough to make most seed investors pass.

The breakthrough came from an unexpected direction. One of the VPs from the original hackathon had moved to a new company — a large professional services firm — and had been using the prototype informally to think through an organizational design challenge. When she moved, she brought Reyes in to run a formal diagnostic for the new organization. The engagement was not a sales motion. It was professional advice. But the output was compelling enough that the firm's CHRO became an informal champion and introduced Reyes to three investors in her personal network who were specifically interested in enterprise HR technology.

Two of those introductions led to term sheets within six weeks. Reyes closed his seed round of $3.2M from one of them in month 14. The Series A closed in month 18, led by a growth equity firm that had been tracking the category for 18 months and had narrowed their thesis to exactly the kind of organizational intelligence platform that Reyes had built. The $40M check was the result of a process that had started, in the investor's words, before Reyes had approached them.

What the Story Actually Teaches

"People want the hackathon story," Reyes says. "They want the 48 hours that changed everything. But the 48 hours gave me an idea that almost didn't work, on a timeline that almost killed the company, in a fundraising environment that rejected me 47 times. The Series A happened because of 18 months of consistent execution in the direction of something I genuinely believed in. The hackathon is a good story. The 18 months is the actual lesson."

He is now 22 months post-Series A, with a team of 60 and a product deployed at seven enterprise customers across financial services, professional services, and healthcare. The privacy concerns that caused early investor rejections have become a competitive advantage: the zero-individual-data architecture that he was forced to build by necessity is now the primary reason regulated industries trust the platform in a market where organizational analytics tools with looser privacy postures are drawing regulatory attention.

The 47 rejections, he says now, were information. Not all of it was accurate — some of the objections reflected investor pattern-matching rather than real insight into the market. But enough of it was accurate that the company he built by month 18 was substantially different from, and substantially better than, the company he would have built without the resistance. "Rejection is feedback," he says. "You have to decide, one at a time, which feedback to incorporate and which to ignore. That is the actual skill. Everything else is just work."