The market size of corporate debt has grown to a staggering $34T globally and $11T in the US alone, yet it remains one of the most inefficient and opaque financial markets. The lack of deal data transparency, coupled with significant amounts of manual processes, has led to information asymmetry for borrowers and traders of this paper. Because of this, many borrowers still agree to off-market operational and financial covenants that can lead to significant financial pressure. In turn, many traders do not have insight into the true risk of the paper they trade.

As complexity and deal speed increase, the desire for deeper insights into these transactions only continues to grow for lawyers, financial analysts, corporate finance teams, and traders. While many companies have tried to find ways to close the data gap in the corporate debt market, we believe AI has finally ushered in the opportunity to do so, and Noetica just raised a $22mm Series A from Lightspeed to take this problem head-on.

Noetica uses proprietary ML models and NLP frameworks to ingest thousands of capital market deal documents, identify the key deal terms, and benchmark those against the rest of the market. This allows deal professionals to more thoroughly analyze, visualize, and understand the risk of a given transaction or group of transactions, within minutes, versus hours our days. 

In only 18 months, Noetica’s platform has analyzed $350B of transactions and indexed >100mm capital markets terms. In doing this, Noetica has built the industry's largest knowledge graph of corporate transaction terms, which will grow as the platform is used on more deals. Noetica has created the best platform for debt professionals to understand and benchmark corporate debt transaction terms. Our belief is this data will be revolutionary for not just understanding the underlying risk in a transaction by deal professionals and borrowers but for the potential to reprice that risk in the market. 

When we met Dan, Yoni, and Tom ahead of them joining the Company Ventures’ Founder Residency program, Grand Central Tech, in the spring of 2023, it was clear the team had the unique mix of subject matter expertise needed to transform corporate transactions. Dan was an experienced attorney from Wachtell who had worked on some of the largest financing and restructuring deals with the unique perspective of being on the other side of the table at BlackRock. Tom was a distinguished machine learning researcher at Columbia, having authored research on improving NLP models’ data usage. Yoni was an experienced operator who had spent time at Deloitte and Liberty Mutual. Each of their backgrounds plays a crucial role in what has made Noetica successful. 

We doubled down from our earlier Seed investment in the Series A because we believe the team can leverage their knowledge graph of capital markets terms to become the industry standard for understanding risk within a corporate debt transaction or portfolio. At Company Ventures, we believe that machine learning and AI models will continue to unlock opportunities to accelerate and automate workflows across all professions for the next decade. Noetica has long known what many are discovering more recently: combining semantic knowledge graphs with powerful AI models unlocks unique capabilities to search and analyze documents at scale. Like them, we are bullish on that future. If you are building a company or exploring ideas at the intersection of machine learning or large language models with capital markets and legal tech, we would love to hear from you. jonny@companyventures.com