Why We Invested in DataRobot
Updated: Aug 26, 2021
Deal Team: Victoria Cheng, Brett Sleyster
DataRobot recently announced its $300MM Series G. We have had the pleasure of knowing the team at DataRobot for the past 5 years and were thrilled to have PruVen Capital become an investor last year in what we see as the leading AI/ML startup in the space. We are excited to partner with a company that is revolutionizing how large enterprises engage with artificial intelligence (AI) and machine learning (ML), and wanted to share our thesis on why we invested below:
Machine Learning at Scale will Become Ubiquitous Across Industries
While companies like Netflix, Amazon, Google, Uber, and Airbnb are well known for becoming market leaders using AI/ML technology, it is increasingly accepted that use of AI and ML will be critical across all major industries. According to IDC, the market for AI technology is expected to grow by more than 18% a year to $37.9bn by 2024. DataRobot is a market leader at the forefront of making this technology more accessible and is well-positioned to capture existing opportunities to benefit from the tailwinds in the space. As creating superior models faster allows firms to target more valuable customers and service them better over time, AI/ML used well will create sustainable competitive advantages that are often core to long-term strategy. We see a future where most business decisions will be enhanced with data-driven models.
As companies across industries look to make this dream a reality, DataRobot provides the needed infrastructure for companies to accomplish this. The company's strong value proposition as well as the versatility of its product suite is highlighted in its large client base of leading enterprises across sectors, including insurance, transportation, manufacturing, CPG, banking, healthcare, and retail. Its clients include over a third of Fortune 50 companies such as Kroger, Nationwide, Lenovo, PNC, and many others.
But Access to Data Scientist Talent is Limited
While demand for AI/ML technology grows at an extraordinary pace, the amount of talent required has not kept up. According to Deloitte, even among companies that are seasoned (i.e. more sophisticated and experienced) in their work with AI, 48% of them say they have a moderate or larger skills gap in meeting the needs of their AI projects. DataRobot significantly reduces the amount of internal expertise required to get high-quality models up and running within large enterprises by automating and abstracting parts of the data scientist’s work to both 1) enable data scientists to do more and 2) make these advanced analytical tools accessible to non-data scientists. All of this leads to allowing for the adoption of AI/ML at greater scale within the enterprise.
The Solution is to Democratize Access to AI and ML
With DataRobot, companies can easily test hundreds of open source and proprietary algorithms to find the best fit. Ultimately this allows business analysts to deploy advanced analytics with ease and speed, something that was previously inaccessible to most. The result is the analysts closest to the data and the business use cases are empowered to leverage these tools. For small teams of data scientists, it enables them to focus their time on the more sophisticated aspects of model development and solve more business problems. DataRobot also makes it simple for other company stakeholders such as IT, risk and compliance, business end-users, and senior executives to use and understand the output from the models.
A Full End to End Platform and Leading the Future of Ethical ML
Over the years, we have watched DataRobot build both depth and breadth in their product offering. The company is capable of managing AI/ML models for a wide variety of data types, and its platform is capable of managing the entire lifecycle for machine learning from data prep to ML ops. The company is also at the forefront of ethical ML and building sophisticated tools to understand bias.
Led by a Phenomenal Team
The team at DataRobot has been executing on the vision of helping people optimize the world using data for nearly a decade now. They have built the organization to over 1,000 employees and more than 500 engineers and data scientists while developing lasting partnerships with leading organizations across the globe.
It has been an absolute pleasure to have been a part of the journey that this incredible team has taken, and we continue to be bullish on what is to come.