Kumo.AI: Predictive ML in Action – Delivering Business Impact Across Industries

Kumo.AI Enters General Availability

Last month, Jure Leskovec, Co-founder and Chief Scientist at Kumo, unveiled the revolutionary Kumo.AI platform, marking a significant milestone in reshaping the landscape of the machine learning lifecycle. Kumo.AI stands out as a paradigm shift, leveraging graph neural networks to conduct end-to-end predictive analytics, from prototyping to production, in a declarative manner. See Prof. Jure Leskovec’s presentation on “Revolutionizing Predictive Machine Learning: Unveiling Kumo.AI’s Game-Changing Release,” watch it here.

Tailoring AI Solutions to Unique Business Needs

Prof. Leskovec introduced the General Availability of the Kumo.AI platform, strategically designed to address the limitations of generative AI. While generative AI has made commendable strides in image and natural language understanding, its one-size-fits-all approach falls short in domain specificity, predictability, and harnessing an enterprise’s private data.

Organizations today are looking for AI solutions tailored to their specific needs—solutions capable of answering crucial business questions. From product/content personalization to fraud detection, the demand is for AI that can be trained for specific tasks, learn from data, and complement the capabilities of generative AI. The key task-specific use cases critical for organizations include:

• Product/content personalization
• Next best marketing action
• New customer acquisition
• Customer loyalty & retention
• Optimizing app notifications
• Fraud detection
• Entity resolution, search, and retrieval
• Forecasting

In response, the Kumo.AI platform empowers organizations to rapidly build task-specific AI models that seamlessly integrate with private data. Kumo facilitates the swift development of task-specific AI solutions, delivering better AI, faster.

Kumo.AI’s Strength: Transforming Relational Data into Accurate Predictions

Kumo’s strength lies in its focus on relational data—structured tables linked with primary and foreign key relations. Whether in e-commerce, finance, or social media, these interconnected tables house a wealth of information. Traditionally, building AI over such data involves labor-intensive processes such as training data generation, feature engineering/experimentation, feature store creation, and complex AI pipelines.

Kumo.AI disrupts this traditional approach by enabling organizations to work directly with their relational data. Using a deep graph neural network that learns directly over all relational data, Kumo.AI eliminates the need for these traditional steps. Simply bring in your relational data, and Kumo learns directly from it, providing task-specific models without the need for repetitive data engineering and model development. This leads to better results out of the box, with the option for experienced ML practitioners to fine-tune every aspect for advanced model iteration.

For organizations, adopting Kumo.AI translates to:

• BETTER: Improved model performance (no feature engineering)
• MORE: Delivery of more models/use-cases
• FASTER: Shortened time to ROI and payback
• CHEAPER: Simplified infrastructure & optimized costs (no pipelines, no feature stores…)

Realizing Results: Kumo.AI in Action

Recent case studies conducted by Kumo’s data scientists showcase how the Kumo.AI platform delivers exceptional predictions rapidly and at a fraction of the costs of comparable approaches. The case studies include:

1. On-Demand Delivery Service: Achieved a 40% improvement in merchant recommendation performance in just 4 days using Kumo’s platform, demonstrating the platform’s ease-of-use and context-aware recommendations. Read the detailed case study here
2. Leading Online Bank: Leveraged Kumo’s platform to predict user intent for targeted next best actions, achieving a 73% precision@12 for new item recommendation. The case study highlights Kumo’s ability to solve complex multi-label classification problems. Read the detailed case study here
3. Fortune 500 Food Delivery Service: Personalized push notifications, achieving a 1% conversion improvement, a statistically significant increase in MAU, and a $100M increase in GMV, while reducing serving costs by 80%. Read the detailed case study here
4. Global Payments Company: Built two production models for predicting customer churn within two weeks, achieving a 20% accuracy boost. The company rated Kumo.AI with a net promoter score of 10. Read the detailed case study here
5. Grocery Chain: Improved personalized product recommendations, achieving 24% and 7% lifts in precision for new and repeat item recommendations, with a production-ready model delivered in just one week. Read the detailed case study here

Experience the Kumo.AI Advantage: 3-Week Trial

Explore the transformative impact of Kumo on your AI initiatives. Qualified companies are invited to apply for the opportunity of a 3-week trial. Don’t miss out—supercharge your machine learning capabilities with Kumo today! Apply here