Kumo.AI has raised $37.0M in total across 2 funding rounds.
Kumo.AI's investors include A* Capital (A Star Capital), Coatue, Creandum, Founders Fund, General Catalyst, LGF, Lightspeed Venture Partners, Lowercarbon Capital, Northzone, Redpoint Ventures, Sequoia Capital, SV Angel.
Kumo.AI is a SaaS AI platform that enables businesses to build and deploy predictive AI models directly on relational data in modern data warehouses like Snowflake, Databricks, or BigQuery, eliminating manual feature engineering.[1][4][5][6] It serves data scientists, engineers, and enterprises in sectors like e-commerce, finance, and tech, solving the core problem of turning complex relational data—such as customer transactions, inventory, and user interactions—into actionable predictions for use cases including fraud detection, recommendations, risk scoring, and customer personalization.[2][3][5] Kumo leverages graph neural networks (GNNs), relational deep learning (RDL), and large language models (LLMs) to automate graph creation from raw data, delivering up to 20x faster model development, real-time predictions, and superior accuracy (e.g., 5.4x lift in conversions, 142% better fraud prediction).[3][4][5] Named to Inc. Magazine’s Best in Business list for 2025 (Best Startups), its models power mission-critical apps serving over 1B users at companies like Reddit, DoorDash, iFood, Sainsbury’s, and Chime, with strong growth via a 2021 Sequoia-led Series A.[1][3][5][6]
Kumo was founded in 2021 by AI executives from Pinterest, Airbnb, LinkedIn, and Stanford researchers, who had spent five years developing its core graph-based AI tech through Stanford/Dortmund labs and the open-source PyG library (now used by NVIDIA, Spotify, and others).[1][5] The idea emerged from recognizing a key gap: relational data in warehouses is businesses' most valuable asset, yet traditional ML requires painful feature engineering, limiting AI adoption.[4][5] Pivotal breakthroughs included Relational Deep Learning (RDL) to convert relational data into graphs for GNNs/graph transformers, and seamless integration with data stacks.[5] Early traction came via Sequoia Capital partnership in 2021 ($18.5M Series A) and adoption by high-scale users, evolving from research prototypes to a production platform handling terabyte-scale data securely.[1][2][4]
Kumo rides the explosive growth of AI on enterprise data stacks, where modern warehouses hold petabytes of relational data untapped by traditional ML due to engineering bottlenecks.[4][5] Timing is ideal amid the GNN/LLM boom and data mesh trends, as companies shift from sampled BI to full-scale predictive AI for personalization, fraud, and revenue ops—fueled by tools like Databricks and Snowflake.[2][6] Market forces favoring Kumo include rising data volumes, regulatory demands for secure in-environment processing, and the need for 10-100x faster ML amid talent shortages.[2][4] It influences the ecosystem by democratizing graph AI (via PyG heritage), accelerating startups/enterprises like Reddit in ads and Sainsbury’s in retail, and bridging data platforms with production AI, potentially redefining "data as the new oil" for business outcomes.[1][3][5]
Kumo is poised to dominate predictive AI for relational data, expanding from core GNN/RDL to agentic workflows, multimodal data, and deeper integrations with emerging stacks. Trends like real-time AI agents, federated learning, and warehouse-native ML will amplify its edge, especially as enterprises prioritize explainable, scalable predictions over black-box LLMs. Its influence could grow via more open-source contributions and Fortune 500 wins, solidifying Sequoia-backed momentum into a category leader—unlocking AI's full potential from everyday business data.[1][5][6]
Kumo.AI has raised $37.0M across 2 funding rounds. Most recently, it raised $18.0M Series B in September 2022.
| Date | Round | Lead Investors | Other Investors |
|---|---|---|---|
| Sep 1, 2022 | $18.0M Series B | A* Capital (A Star Capital), Coatue, Creandum, Founders Fund, General Catalyst, LGF, Lightspeed Venture Partners, Lowercarbon Capital, Northzone, Redpoint Ventures, Sequoia Capital, SV Angel, Y Combinator, Aaron Levie, Julia Hartz, Kulpreet Singh, Max Mullen, Ryan Tedder, Zachary Sims | |
| Apr 1, 2022 | $19.0M Series A | Acequia Capital, AlleyCorp, Bling Capital, Catapult Capital, Change Ventures, Contrarian Ventures, Dreamers VC, FJ Labs, Greylock, Khosla Ventures, L Catterton Growth, Lowercarbon Capital, Moxxie Ventures, Pareto Holdings, Scribble Ventures, Streamlined Ventures, SV Angel, Tapas Capital, Tealium, Two Small Fish Ventures, Adrian Aoun, Akshay Bhargava, Ameet Ranadive, Avid Larizadeh, Ben Porterfield, Bob Young, Bradley Horowitz, Evan Moore, Gokul Rajaram, James Blouzard, Jason Tolkin, Jon Runyan, Joshua Schachter, Kevin Lin, Kevin Weil, Louis Beryl, Mantas Mikuckas, Markus Villig, Martin Henk, Martin Villig, Max Mullen, Mike Kourey, Ott Kaukver, Pete Koomen, Ragnar Sass, Richard Branson, Rohini Pandhi, Ryan Carlson, Ryan Tedder, Scott Belsky, Steve Chen, Thomas Plantenga, Varsha Rao, Vibhu Mittal |
