Nvidia acquired Kumo AI for over $400 million, per The Information. The deal targets a gap LLMs have left: predictions from relational database data, not just documents and code.
Key facts
- Deal valued at more than $400 million.
- Kumo raised $37 million from Sequoia Capital and others.
- KumoRFM outperforms gradient-boosted trees on RelBench benchmark.
- Fine-tuning lifts results by 10% to 30%.
- Customers include DoorDash, Reddit, and Snowflake.
Nvidia has acquired Kumo AI, a four-year-old startup that builds foundation models for making predictions from business data, Fortune reported on June 3. The Information pegged the deal at more than $400 million. Kumo's three co-founders — CEO Vanja Josifovski, engineering head Hema Raghavan and Stanford professor Jure Leskovec — moved to Nvidia in May, though neither company has formally announced the transaction.
Why Kumo's Technology Matters
Kumo's core model, KumoRFM, is a pre-trained relational graph transformer. It represents a database as a graph, where every record becomes a node and primary-foreign key links become edges. Because the model was pre-trained on thousands of real and synthetic relational datasets, it can make predictions on a database it has never seen, without task-specific training. Users define the prediction — such as which customers will churn in the next 30 days — through a lightweight query language.
On the RelBench benchmark, which spans 30 predictive tasks across seven domains, Kumo reports that the zero-shot model outperforms gradient-boosted trees built with hand-crafted features, and that fine-tuning lifts results by a further 10% to 30%. The startup, backed by $37 million from investors including Sequoia Capital, shipped a second-generation model in April and counts DoorDash, Reddit and Snowflake among its users.
Strategic Implications
The acquisition follows a familiar pattern. Nvidia bought Run:ai for roughly $700 million to own GPU orchestration, picked up the data semantics startup Illumex, and signed the Groq agreement for low-latency inference. Each deal moves Nvidia further from selling chips and closer to owning the software enterprises run on those chips. Kumo extends that motion into predictive analytics, a market served today by gradient-boosted tooling, AutoML vendors and the machine learning services of AWS, Google Cloud and Microsoft.
The deal also creates an awkward dynamic for Snowflake and Databricks, which position their platforms as the natural home for machine learning on enterprise data and now find a prominent predictive AI vendor inside the company they depend on for accelerated computing.
The Challenges Ahead
The evidence for KumoRFM's accuracy comes almost entirely from Kumo's own benchmarks. Independent validation will be critical. Additionally, enterprise adoption of predictive AI on relational data has historically been slow, with most companies still relying on SQL-based analytics rather than ML pipelines. Nvidia will need to integrate Kumo into its existing software stack — possibly through NeMo or CUDA — to drive adoption at scale.
What to watch
Watch for Nvidia's integration of KumoRFM into NeMo or CUDA by Q4 2026, and whether Snowflake or Databricks respond with their own predictive AI acquisitions or partnerships.
Source: forbes.com
