In 2016, Atlas, the AI company I co-founded with funding from Bill Gates, was acquired by Xinova. Xinova wanted two things: our team, one of the few with hands-on experience building production AI systems at the time, and the semantic search IP we had developed at Atlas. Both would become foundational to what Xinova was trying to build.
Xinova had been founded on a premise I found immediately compelling: that valuable ideas exist outside the organizations that need them and have the means to monetize them. At the same time, large R&D organizations inevitably generate IP that is valuable beyond their parent company's core business. The opportunity was to build the infrastructure that connected those two realities — a global marketplace where breakthrough ideas could find the enterprises best positioned to bring them to market, and where corporate innovation challenges could reach the world's best inventors rather than just the ones already in the room.
The traditional IP brokerage model was too slow, too fragmented, and too dependent on relationships and geography to serve that opportunity at scale. Xinova was built to replace it.
Xinova
What we built
Xinova was designed as a four-sided innovation marketplace connecting Talent, Technology, Capital, and Market. The platform used AI-driven matchmaking to connect enterprises with a global network of inventors, scientists, and investors — bringing the semantic matching intelligence developed at Atlas to bear on one of the most complex matching problems in the innovation economy.
Key capabilities included AI-powered matchmaking between enterprise challenges and inventor networks, pre-vetted IP assets to reduce time-to-market, and AI-powered smart contract management to streamline agreements and collaboration. We launched Arcnet, an online capital marketplace developed with Asymmetric Return Capital (ARC), to support innovation investors and close the funding gap between promising IP and market-ready ventures.
The platform's most tangible expression of the model was SousZen: a joint venture co-created with PepsiCo that combined supply chain expertise with smart appliance technology to disrupt mobile food services. SousZen wasn't just a customer engagement — it was proof that the marketplace model could produce new companies, not just transactions.
The shift Xinova represented was fundamental: from passive IP brokerage, where deals happened when the right people happened to know each other, to proactive innovation-as-a-service, where AI continuously identified and connected the right talent, technology, and capital to the right market opportunity.
What it delivered
Xinova scaled to more than 12,000 inventors across 118 countries, serving enterprise clients including PepsiCo, Honda, Samsung, Siemens, and Airbus.
Within six months of the platform's redesign and relaunch: membership grew 230%, conversion from RFI to submission increased 42%, submission-to-selection time decreased 60%, and overall network activity increased 56.8%. Two ventures were spun out with private equity funding — including SousZen with PepsiCo — validating the marketplace model's ability to generate not just matches but companies.
My Role
I joined Xinova through the acquisition of Atlas, bringing a team with rare AI experience and the semantic search technology that would power the platform's matchmaking engine. From that position I took on broad product and strategic leadership — shaping not just what Xinova built but how it thought about the problem it was solving.
On the product side, I defined and drove the vision, roadmap, and detailed requirements for the platform. I designed and launched personalized portals for customers, members, investors, and partners — four distinct user populations with fundamentally different needs, mental models, and definitions of value, all of whom had to find the platform trustworthy and worth returning to. I built the comprehensive design system and solution review tools that gave the platform coherence at scale, and developed the smart contract workflows that made the agreement process fast enough to match the pace of the innovation opportunities the platform was surfacing.
Standardizing workflows and prototyping processes reduced innovation cycles by 60% — not by cutting corners but by eliminating the ambiguity and rework that had been slowing the team down.
On the business side, I led M&A initiatives focused on network expansion, launched Arcnet, and co-created SousZen with PepsiCo — taking a joint venture from concept through formation to a funded, operating company. I established the product management, UX design, and user research functions that gave the organization the capability to build at the level the market required, and partnered with engineering and HR to scale a distributed development organization from inception to more than thirty employees in twelve months.
When it became clear that the core marketplace model wasn't achieving the commercial traction the business needed, I made the decision to move on and start Zeitworks — taking the process intelligence insight that had emerged from watching how work actually flowed inside enterprise organizations and building a company specifically designed to address it.
That decision was not a retreat. It was the next conviction.
D E E P D I V E
The Battleship Principle
The insight that shaped the platform's core design logic was the same one that drives good strategy: knowing where not to look is as valuable as knowing where to look.
Every constituency on the platform faced a version of the same problem. Enterprises could waste months pursuing innovation in spaces that were either too crowded, economically unviable, or outside their addressable market. Inventors could invest significant time developing solutions in areas already saturated with patents, making commercialization prohibitively expensive before it had even begun. Investors could allocate attention and capital to opportunities that looked promising in isolation but had no viable path to the market. Technology owners could pursue licensing conversations that were structurally incompatible with what potential partners were actually able to agree to.
The Battleship graph was designed to solve this before it happened. Named for the board game — and the premise that knowing where your opponent's ships aren't is as important as knowing where they are — the visualization mapped the landscape of each opportunity space across two dimensions: market viability and competitive density. Crowded spaces, economically constrained spaces, and spaces outside a party's market or capability were flagged clearly, giving every user the same view of where not to invest their attention before they committed to a direction.
For enterprises, it cut wasted R&D spend by redirecting innovation challenges toward spaces where viable, protectable solutions were actually possible. For inventors, it protected them from pursuing dead ends. For investors, it surfaced the opportunities with genuine white space. The same visualization, serving four different users, solving four versions of the same problem.