Workday launches a venture capital arm to invest in machine learning and data science startups

Enterprise software company Workday is launching a venture fund aimed at early to growth stage startups that are leveraging machine learning and data science to solve enterprise-level problems. In conjunction with this announcement, Workday is also naming the first four startups it has invested in.

Run by Adeyemi “Ade” Ajao, the company’s vice president for technology product strategy, Workday Ventures will invest in companies on a strategic level, meaning that it doesn’t seek to receive any financial gain or lead any rounds. Rather, Ajao told VentureBeat, the objective is to help its portfolio companies and establish an ecosystem. The company wants to learn from all of its startups and will not limit itself on how much it will fund these companies.

[aditude-amp id="flyingcarpet" targeting='{"env":"staging","page_type":"article","post_id":1767125,"post_type":"story","post_chan":"none","tags":null,"ai":false,"category":"none","all_categories":"business,","session":"A"}']

The exact amount of the Workday Ventures fund was not disclosed, nor how much the company would invest in each round.

The first four companies that Workday is investing in span a wide array of industries:

• Jobr is a mobile-only job aggregator that lets users browse and apply for jobs without the hassle of a formal job search. It leverages Tinder-like behaviors to learn and recommend the best positions for candidates from more than a million job postings that users can instantly apply for.
• Metanautix “simplifies the big data supply chain” by enabling users to combine and search through unstructured, structured, and relational data sources with a single analytics engine using industry standard SQL. It raised $7 million in funding last August.
• ThinAir is an intelligent security platform built to allow enterprise users to manage their “most sensitive” data in a way that it claims “enhances, not hinders” productivity.
• Unbabel is a web translation service combining machine learning and human crowdsourcing to provide accurate, human-quality translation.

The story of the origin of Workday Ventures is perhaps the same as most corporate investment vehicles. Ajao said that following the debut of Insight, the company received a “flood of inbound requests from entrepreneurs.” After speaking with them, Workday realized that these startups came up with “powerful stuff,” but had no support within the machine learning industry.

While Workday Ventures is notable, it’s not the first time Workday has made investments in companies. In June, it participated in Tidemark’s $25 million series F as well as Datameer’s $19 million series D. Its creation also follows other corporations seeking to build better relationships with startups, including Twitter, Salesforce, HP, Samsung, and many others.

Workday will invest in companies that are trying to solve enterprise-level problems, but at their core are using machine learning or data science to do so. Funded startups will receive access to Workday’s customers if Workday likes what the startup is doing and also can pair up with Workday’s engineering team for technical transfers.

Ajao shared that while four investments have been made, his team has already met with more than 30 companies. He has set a goal of closing this year with 10 to 12 investments made.

If you’re a startup looking to receive a strategic investment from Workday, your best bet of receiving funding involves being focused on the enterprise, using machine learning or data science, and being at a stage where Workday can not only help you, but also work with you. Should Workday be interested, Ajao said that all decisions will be made quickly — it will take less than a week for an answer and slightly longer for any deal to be executed.

Adding to the news mix today, Workday also shared that it has acqui-hired Upshot, a mobile-focused business intelligence startup that was a co-winner in Salesforce’s $1 million hackathon in 2013.

[aditude-amp id="medium1" targeting='{"env":"staging","page_type":"article","post_id":1767125,"post_type":"story","post_chan":"none","tags":null,"ai":false,"category":"none","all_categories":"business,","session":"A"}']