Breaking News: The Startup That Will Lead Predictive AI for All was just born

Breaking News: Sequoia Leads Series A Funding in the company that Will Lead Enterprise SaaS Prediction

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Predictive AI for All: a small new startup called Kumo is coming to bring it!

Hey Guys,

As some of you know I’m obsessed with the Venture Capital space when it comes to companies that leverage A.I. From Softbank led startups to Sequoia’s picks both in China and elsewhere, I do my best to follow the trends.

I have a sense that this company will become important in how we leverage Prediction in the future of business.

Led by Sequoia Capital in Series A Funding, Kumo has emerged from stealth mode. Kumo, a San Francisco, CA-based new SaaS AI platform for the modern data stack that allows businesses to make faster, simpler, and smarter predictions, announced it has emerged from stealth with $18.5 million in Series A funding.

Read Blog post from Sequoia

Democratizing AI on the Modern Data Stack!

Kumo will use the new funding to continue its hiring efforts, scale its leading AI technology, and invest in R&D efforts to expand its platform and services. Their LinkedIn profile says the company was founded in 2021.

The team behind PyG (PyG.org) is working on a turn-key solution for AI over large scale data warehouses. They believe the future of ML is a seamless integration between modern cloud data warehouses and AI algorithms.

Their ML infrastructure massively simplifies the training and deployment of ML models on complex data. With over 40,000 monthly downloads and nearly 13,000 Github stars, PyG is the ultimate platform for training and development of Graph Neural Network (GNN) architectures. GNNs -- one of the hottest areas of machine learning now -- are a class of deep learning models that generalize Transformer and CNN architectures and enable us to apply the power of deep learning to complex data. GNNs are unique in a sense that they can be applied to data of different shapes and modalities.

Think about it.

Query the future.

Unleash the predictive power of enterprise data.

• Companies spend millions of dollars annually to store terabytes of cloud data—but leverage only a fraction of it for predictive tasks. With Kumo, businesses can unleash the full potential of their enterprise data for faster, simpler, and smarter predictions. Today, in SQL, you already query the past; with Kumo, you can query the future.

The reason I am bullish on this trend is how Sequoia explained it on their blog:

"As our conversations continued, we kept coming back to the fact that companies spend untold billions storing their data in warehouses and lakes, all with the hope of making better business decisions. Yet today, those decisions are possible only for a select few enterprises who can afford to recruit and retain AI teams—and even those teams are constantly overwhelmed with work and tool sprawl. As experienced AI leaders themselves, all three of Kumo’s co-founders understand this firsthand.

Of course, data warehouses themselves once faced similar issues—until Snowflake came along. What if there were a platform that was just as accessible and easy to use, but for graph-based AI, so a company could load it up and immediately start making faster, smarter predictions? It was an exciting idea, and we knew it would be amazing—if it were technically possible. What the co-founders were proposing was an extremely difficult feat of engineering. 

But another year and a team of 20 later, Jure, Vanja and Hema are making that vision reality. Some of the best graph neural networks engineers out there have come together to bring AI not just to one company but to everyone. As Kumo continues to grow the team, scale its tech and invest in R&D, this Series A round is just the latest milestone in what we at Sequoia believe will be a decades-long partnership."

After Snowflake, Databricks and Datadog, I see Kumo evolving into a company that harness the power of prediction for businesses in a SaaS model. I think the pedigree of the co-founders and the timing is right. (This is not a sponsored post and only represents my opinion).

Their Mission

• Their mission (as of April 7th, 2022) is to bring the most powerful graph learning approaches, proven in the research world, to all enterprise data—through simple and elegant tooling.
• They are passionate about the possibility and promise of graph learning. The company believe they can scale enterprise prediction by orders of magnitude, while also dramatically widening the circle of people who can effectively use predictive AI.

The founders

• Jure Leskovec (Stanford)
• Vanja Josifovski (Kosei, acquired by Pinterest)
• Hema Raghavan (Growth AI at LinkedIn)

Kumo.AI is an innovative SaaS AI platform for the modern data stack that allows businesses to make faster, simpler, and smarter predictions.

What I find exciting is how prediction will change the business landscape in the next twenty years and companies like Kumo could drive it. Here there’s a big mission to change how businesses make better, smarter, and faster predictions by leveraging predictive #AI with #graphlearning. In fact their ties to Stanford, Pinterest and LinkedIn will also draw a lot of talent more easily to their startup.

In an era where the Cloud and Enterprise AI is fastly maturing here then is a sweet spot or low-hanging fruit. Even as data warehouses themselves once faced similar issues in need of an enterprise leader—until Snowflake came along. What if there were a platform that was just as accessible and easy to use, but for graph-based AI, so a company could load it up and immediately start making faster, smarter predictions?

Is Kumo the SaaS Snowflake of Prediction? Maybe, maybe not. It’s also interesting to witness how the venture capital momentum cycle works. The round was led by Sequoia Capital, with additional participation from A Capital, SV Angel, Ron Conway, Igor Perisic (Google), Li Fan (CTO, Circle), Tristan Hardy (CEO, dbt Labs), Sridhar Ramaswamy (CEO, Neeva), Greg Greeley (President & COO, Opentrons), Rob Eldridge (Tapas Capital), David Chaiken (Chief Architect, Pinterest), and Cory Scott (CISO, Confluent). 

The Opportunity

As A.I. in the Cloud is flourishing it opens up new possibilities. To run useful AI predictions on the data often requires untangling the web of data connections. The new Stanford-bred startup says it has a solution using a new class of artificial intelligence to solve that problem.

Kumo then was founded around December, 2021. The Mountain View, California-based startup was launched four months ago (according to Forbes) by founders Vanja Josifovski (formerly chief technology officer at Pinterest and Airbnb’s Homes business), Hema Raghavan (an ex-LinkedIn engineering director) and Stanford professor Jure Leskovec, who was also previously Pinterest’s chief scientist.

The company comes as the culmination of five years of academic research conducted by a Stanford team featuring Leskovec, in conjunction with Germany’s Dortmund University.

The A.I. Predictive Advancement?

They focused on a budding form of AI, termed “graph neural networks,” which approaches machine learning by treating the data as if it were a complex graph network. Older forms of neural networks have become good at tasks with “structured data,” like image recognition or speech detection, but are hampered by data with unordered connections.

Gentle Intro to Graph Neural Network

PyG is the world’s most widely-used graph learning platform and its core technology underpins Kumo’s closed-source enterprise product. See on GitHub.

Moving forward, their going to be focusing on growing their amazing team. If you are a Distributed systems Engineers, Applied ML Engineer, or GNN Expert, you can always send them an email at jobs@kumo.ai

If you have read Substack’s own The Pragmatic Engineer, I think you know how lucrative these first few engineering roles can be. 

So far, some of the best graph neural networks engineers out there have come together to bring AI not just to one company but to everyone, according to Sequoia. As Kumo continues to grow their team, and scale its tech and invest in R&D, this Series A round that was announced April 7th, 2022 is just the latest milestone in what we at Sequoia believe will be a decades-long partnership.

Company: Kumo.AI Inc.

Raised: $18.5M

Round: Series A

Funding Month: April 2022

Lead Investors: Sequoia Capital

Additional Investors: A Capital, SV Angel, Ron Conway, Igor Perisic (Google), Li Fan (Circle), Tristan Hardy, Sridhar Ramaswamy, Greg Greeley, Rob Eldridge, David Chaiken, and Cory Scott 

Company Website:

 https://kumo.ai/

Software Category: Predictive AI

Conclusion

If you are interested in watching Kumo grow up simply follow and tap on the notification bell of some of the people involved (I linked some of their names to their LinkedIn profiles). You can also follow Konstantine Buhler, of Sequoia Capital. So long as AiSupremacy is in existence, we are going to watch AI startups that we cover grow up. Aibee is another from Sequoia China.

Most companies pay hundreds of thousands to millions of dollars every month to store terabytes of data they collect about their products and customers. Yet these businesses are only able to leverage a tiny fraction of this data for predictive tasks. Kumo (in the 2020s) might just develop the solution to this.

Founded by several pre-eminent AI executives from companies like Pinterest, Airbnb, and LinkedIn, the core technology that underpins Kumo’s product has been in development for the past five years through Stanford/Dortmund labs and PyG open-source software.

I like how this startup encapsulates the new trend of Graph Neural Networks to solve prediction problems.

If you are a company and you want to sign up for our Kumo beta, visit www.kumo.ai/#beta.

I think this could evolve into bleeding edge enterprise tech. The company’s software leverages the tech from PyG as the foundation for its software that helps customers to more easily craft complex predictive models from their business data.

It also has vague echoes of AI for Good movement popular at Microsoft and Google about democratizing AI for all. Interestingly enough Kumo’s product thus far is designed primarily for data analysts and data scientists, and Josifovski says it should be usable even for employees without tech expertise.

However the startup is pre revenue and will likely use a subscription SaaS model. It won’t be easy to scale the company however. Companies valued in the billions of dollars, like Databricks, DataRobot and Dataiku, have already established lucrative businesses on different approaches to data science, notes Forbes.

Evolution of the Social Graph and Prediction in the Metaverse

The research led to the development of PyG, an open source tool for graph neural network learning that was first launched five years ago. In the intervening time, Kumo’s founders implemented the technology at Pinterest and LinkedIn.

“LinkedIn is like one big graph,” as Josifovski, the CEO, puts it, before contending that graph neural networks have “the potential to revolutionize machine learning in a similar way that deep learning revolutionized speech.”

So could graph neural networks really revolutionize predictive machine learning? That’s the promise, what do you think?

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If you enjoy articles about A.I. at the intersection of breaking news join AiSupremacy here. I cannot continue to write without community support. (follow the link below).

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