Berlin Tech Meetup: The Future of Relational Foundation Models, Systems, and Real-World Applications
For Strategy Officers & VPs of Strategy
Competitive advantage requires three things: more accurate predictions than your competitors, knowledge they don't have, and speed to market. KumoRFM delivers all three. It learns from relational structure that flat tables destroy, it's pre-trained on thousands of datasets your competitors have never seen, and it ships production models in hours instead of months.
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Why Strategy Leaders choose Kumo
Here's how Kumo accelerates your highest-priority strategic initiatives from roadmap to measurable business impact.
$100M+
Proven revenue impact
DoorDash generates hundreds of millions in GMV from Kumo-powered recommendations. Your data holds the same untapped strategic value.
Weeks
From strategic initiative to production
No 18-month AI transformation timeline. Deploy your first predictive model in days and scale across the organization in weeks.
55+
Proven use cases across industries
Churn, fraud, recommendations, LTV, demand forecasting — validated patterns you can deploy against your strategic priorities immediately.
Loved by data scientists, ML engineers & CXOs at
In production today
Enterprise Customer
Went from 3 models in production to over 50 in a single quarter with the same team. Feature engineering eliminated, pipeline complexity reduced by 95%.
Databricks
Lead-scoring models delivering dramatic improvement in conversion rates. Deployed in days instead of months, with zero feature engineering.
DoorDash
Restaurant recommendations driving hundreds of millions in GMV. Expanded to notification reranking and send-time optimization using the same foundation.
The challenge you know too well
Path 1 — Internal ML teams: They can only ship 3–5 models per year, each taking months of feature engineering, custom pipelines, and dedicated infrastructure. Your strategic roadmap has dozens of prediction use cases waiting in the backlog.
Path 2 — LLM investments: They generate text and summarize documents, but they don't address structured data predictions — the churn models, lead scores, fraud detection, and demand forecasts that actually move your KPIs.
Kumo bridges the gap between strategic vision and production AI. One platform connects directly to your data warehouse and delivers predictions across every use case on your roadmap — without the 18-month transformation timeline.
95%
Less data preparation
Feature engineering eliminated
10–50%
Accuracy improvement
Over traditional ML (RelBench)
20x
Faster time-to-value
From months per model to hours
55+
Use cases
Validated in production
KumoRFM isn't limited to your data alone. Pre-trained on billions of relational patterns across diverse datasets and fine-tuned to your schema, it sees what no in-house model can. As per the SAP SALT benchmark.
LLM
GPT4 + AutoML
PhD Data Scientist
Feature eng. + XGBoost
KumoRFM
Relational Foundation Model
17x
increase in models shipped per quarter
“Beating internal XGBoost model on key metrics with far less data and features. We went from three models in production to over fifty in a single quarter, with the same team.”
Matt Loskamp
GTM Data Science Leader, Enterprise Customer
From startups to enterprises, leading organizations rely on Kumo to deliver predictive insights at scale.
Peer-reviewed
K. Huang, M. Fey, J. Leskovec et al.
A foundation model for relational data - pre-trained across schemas, it delivers accurate predictions out of the box and improves with fine-tuning on your specific data.
Read paperM. Fey, W. Hu, K. Huang, J. Leskovec et al.
Introduces learning predictive models directly on relational databases, eliminating the feature engineering pipeline that has historically bottlenecked enterprise ML.
Read paperJ. Robinson, R. Miao, K. Huang et al.
An open benchmark for evaluating relational prediction methods across 11 databases and 30 tasks. Kumo consistently outperforms traditional ML baselines.
Read paper
