Seven-year-old enterprise AI company Dataiku reached Unicorn status last year when Capital G (Google Capital) participated in a secondary offering, bringing Dataiku’s valuation to $1.4B. Now, armed with a new round of fresh capital, Dataiku is on a mission to be a leader in the future of AI in the enterprise. Dataiku’s platform provides flexible AI and machine learning solutions that allow the meaningful processing of unstructured data, allowing cross-department collaboration to enrich the data. Dataiku presently has 300+ customers worldwide and the infrastructure is designed so that the platform can be in every industry from retail to pharma; clients include Sephora, Morgan Stanley, Pfizer, and GE Aviation. For example, banks and other financial institutions use Dataiku to detect fraud, generate hyper-personalized financial recommendations, and more. While CPG companies use Dataiku to optimize supply chains. Dataiku was founded on the belief that every company, no matter industry or size, needs to integrate data science, machine learning, and AI in order to innovate and succeed.
AlleyWatch caught up with VP of Finance Ed Bush to learn about the mission of democratizing access to AI for enterprises, the company’s experience fundraising remotely, and Dataiku’s recent funding round, which brings the total funding raised to $246.8M.
Who were your investors and how much did you raise?
We raised a $100M Series D investment round which was led by Stripes, with major investment by Tiger Global Management and participation from existing investors Battery Ventures, CapitalG, Dawn Capital, FirstMark Capital, and ICONIQ.
Dataiku is one of the world’s leading AI and machine learning platforms, supporting agility in organizations’ data efforts via collaborative, elastic, and responsible AI, all at enterprise-scale. Hundreds of companies use Dataiku to underpin their essential business operations and ensure they stay relevant in a changing world, including models driving fraud detection, customer churn prevention, predictive maintenance, supply chain optimization, and much more. Dataiku is built for companies looking to democratize AI across their organization, bringing agility and preparedness to the business through the use of data by everyone from analysts to data scientists.
What inspired the start of Dataiku?
Dataiku was founded in 2013 with the mission to take machine learning and AI projects out of experimental labs and put them into everyday operations that are truly woven into the fabric of a company. At its core, Dataiku believes that in order to stay relevant in today’s changing world, companies need to harness Enterprise AI as a widespread organizational asset instead of siloing it into a specific team or role. To make this vision of Enterprise AI a reality, Dataiku is the only platform on the market that provides one simple UI for the entire data pipeline, from data preparation and exploration to machine learning model building, deployment, and monitoring, and everything in between.
How is Dataiku different?
We believe leveraging AI at a large enough scale to become an organizational asset requires data democratization. That is, data in the hands of the many, not the elite few. As such, we built a platform to enable people wherever and whoever they are (technical or non-coders, data scientists, engineers, architects, or analysts). For our customers, Dataiku serves as the central location for distributed or remote teams, providing resources to work faster and smarter together for a more data-driven organization. The platform was built from the ground up to support usability in every step of the data pipeline and across all profiles, from data scientists to cloud architects to analysts. Dataiku also supports the creation of a spectrum of applications, whether that means building out a self-serve analytics platform or fully operationalized AI integrated with business processes.
What market does Dataiku target and how big is it?
Currently, Dataiku has over 300 customers who understand that a collaborative and end-to-end AI strategy is critical to their success, including Schlumberger, GE Aviation, Sephora, Unilever, BNP Paribas, Premera Blue Cross, Kuka, and Santander, but the potential market is any enterprise who wants to up-level how they apply AI in their business. Dataiku’s centralized, controlled, and elastic environment fuels exponential growth in the amount of data, the number of AI projects, and the number of people contributing to such projects. The platform was built to scale as businesses strive to go from a handful of models in production to hundreds (or thousands). The bottom line is that Dataiku is built for every industry, every use case, and also for everyone.
What’s your business model?
We generate revenue through annual subscriptions to the Dataiku platform.
How has COVID-19 impacted the business?
So many companies and small businesses have been devastated by COVID, and it’s heartbreaking to see. Those are the companies and the people that deserve our attention right now. We sell software to large organizations. It’s critically important software used by critically important companies. We recognize that Dataiku, and our clients, are in a very fortunate position compared to many others.
What was the funding process like?
We didn’t know what to expect. No one on the team had fundraised during a global pandemic before! We braced for a long, difficult process and were pleasantly surprised when it turned out to be pretty quick and without much pain. To get such positive validation from the investor community during such an uncertain time felt great. We try to never take our good fortune for granted, and that’s especially true during such difficult times. We’re happy to be partnering with two additional investors in Stripes and Tiger who truly believe in our mission and who are such a good match for us as we plan for future growth.
What are the biggest challenges that you faced while raising capital?
The global macroeconomic environment is really tough right now, but we’re in a strong position and are growing even as others who are a bit less well-positioned are struggling. Investors recognize our value proposition – this crisis has shown that AI is vital to success for every enterprise – and we were able to show that during the fundraising process. But also, Zoom fatigue. Trying to liaise with prospective investors over Zoom every day for two months, many of whom you’ve never had the pleasure of meeting face to face, wasn’t ideal. We’d have much rather sat across the table from them and connected face to face.
What factors about your business led your investors to write the check?
Ron Shah, Partner at Stripes, said it really well. What our investors see in Dataiku is not only a commitment to developing future-proof technology for customers across industries and geographies, but maybe even more importantly, a team of dedicated professionals around the globe working to ensure trust, safety, and resilience through machine learning. The market has continued to validate Dataiku’s collaborative approach as the best way to reap the benefits of AI throughout any organization, and agility through AI has never been a more important capability in the enterprise.
What are the milestones you plan to achieve in the next six months?
The progression of AI in the enterprise has moved rapidly from experimentation to real-life implementations at scale in 2020. In order to continue to scale, serve our customers, and fill this need to keep up with customers’ AI maturity, we’re working to take our current end-to-end platform offering even further. Each company’s path to Enterprise AI looks different, but as the importance of AI to solve mission-critical business problems is more prominent than ever, we’ll be bringing more solutions, services, and products to our customers to become the AI platform, even as customers start to have hundreds or thousands of models in production. More specifically, we’ve got some exciting new offerings in the works – for example, the ability to create internal applications for use across a variety of verticals and job functions, whether that means building out a self-serve analytics platform or fully operationalized AI integrated with business processes.
Each company’s path to Enterprise AI looks different, but as the importance of AI to solve mission-critical business problems is more prominent than ever, we’ll be bringing more solutions, services, and products to our customers to become the AI platform, even as customers start to have hundreds or thousands of models in production.
What advice can you offer companies in New York that do not have a fresh injection of capital in the bank?
Even if times are hard for your company, try to stand by your employees the best you can. The employees of Dataiku are the reason our product works, our clients are happy, and we’re able to move our vision forward. Without them, we’re nothing, and we never forget that. My advice is to keep working toward your mission and put a special emphasis on finding and keeping the best people you can who will help you make it a reality.
Where do you see the company going now over the near term?
Dataiku plans to use this funding to continue pursuing our mission of democratizing AI in the enterprise. We’ll do that by adding new offerings to our end-to-end platform and growing our team around the world.
What’s your favorite outdoor dining restaurant in NYC
My family has been slow to dip our toes back into outdoor dining in the city. We have someone in our pod who is immuno-compromised as well as a three-year-old who’d rather get up and walk around than observe social distancing. But my wife and I recently stole away for brunch for the first time in a while. We were outside at Tartine in the West Village, and everything in our world felt normal again for that one hour. It was great.
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