Pecan AI, the leader in AI-based predictive analytics for BI analysts and business users, today announced it has raised $66 million in a Series C round led by New York-based global private equity and venture capital firm Insight Partners, with participation from GV (formerly Google Ventures) and existing investors S-Capital, GGV Capital, Dell Technologies Capital, Mindset Ventures, and Vintage Investment Partners. In the last 12 months alone, Pecan has raised over $100 million. The funding will be used to scale Pecan’s global footprint and accelerate research and development of the industry’s only low-code predictive modeling and data science platform.
Sitting at the nexus of AI and data analytics, Pecan’s low-code predictive modeling and data science platform empowers business intelligence (BI) analysts to predict revenue-impacting risks and outcomes. Users can turn massive amounts of raw transactional data into accurate predictions of critical key performance indicators that directly impact revenue and profitability. Over the last year, Pecan has once again more than tripled its annual recurring revenue. This growth is fueled by accelerating customer adoption with midmarket and enterprise companies across fintech, insurance, retail, consumer packaged goods, mobile apps, and consumer services. These companies chose Pecan to unlock transformational improvements in customer acquisition, customer retention and lifetime value, demand forecasting, supply-chain optimization, resource allocation, and pricing and packaging.
“We believe that any company should be able to deploy AI-based predictive analytics, even without data science resources on staff,” said Zohar Bronfman, CEO and co-founder of Pecan AI. “This new funding will help us scale Pecan further to overcome the data science scarcity gap, enabling our customers to move beyond outdated data-mining techniques that offer little value in predicting future outcomes. We are on a mission to unlock the potential of business intelligence and analytics through the power of AI.”
“With the commoditization of data ingest, most companies are finding it challenging to drive insight from the oceans of data they manage,” said George Mathew, Managing Director at Insight Partners. “Yesterday’s legacy platforms are still struggling to truly democratize AI; hiring armies of data scientists to build predictive models is a non-starter. Pecan is a category-defining platform in the use of AI for advanced business analytics to predict all sorts of outcomes – from strategic global demand forecasting to performance of everyday marketing campaigns, and everything in between. We look forward to serving the Pecan team as they scale up.” Mathew will join Pecan’s board.
Pecan’s proprietary AI algorithms optimize and train predictive models to get effective results as quickly as scientifically possible. It is incorporating advanced data science techniques and next-generation automation of data science capabilities across an ever-expanding set of predictive use cases. By simplifying data preparation, automating feature engineering, and creating models refined for high performance in specific use cases, Pecan transforms SQL-trained BI analysts into skilled and effective data scientists who can build accurate predictions in days.
“We are still in the early innings of translating the capabilities of AI into everyday business value,” said Crystal Huang, Partner at GV. “We are thrilled to partner with Pecan on their mission of democratizing access to AI-powered predictions.” Huang will join Pecan AI’s board as an observer.
“Pecan has driven greater efficiency and effectiveness for our demand and supply chain forecasting teams,” said Neil Ackerman, Head of Supply Chain Innovation Hubs for Americas, Europe, Middle East and Africa at Johnson & Johnson. “We witnessed the return on investment within weeks,” shared Thomas Dickey, Director of North America Supply Chain at Johnson & Johnson. “With Pecan’s solution, our forecasting accuracy has improved, especially in our most challenging consumer segments, and we deployed our models to production quickly. We now have a granular understanding of the factors influencing consumer preferences and can adjust our production and distribution to remove variability across the supply chain. We look forward to expanding our partnership further as we focus our efforts on delighting the consumer.”