Handshake, the platform that began its journey in 2013 as a means for hiring college graduates, has recently made headlines with its acquisition of Cleanlab, a company that garnered interest from various AI data labeling firms. This strategic shift seeks to greatly improve Handshake’s talent pool, primarily through an acqui-hire strategy. It would match their increasing focus on that part of the fast-growing human data labeling industry.
Of course, this approach isn’t without a precedent. Just a year ago, Handshake opened its own human data labeling practice to power foundational AI model companies. This new Handshake initiative has so far shown to be successful, with Handshake generating the data for eight of the top AI laboratories, including OpenAI. Through the acquisition of Cleanlab, Handshake hopes to strengthen its expertise in this important area.
Cleanlab, led by its dynamic CEO, formerly received a $1 million grant from Schmidt Futures for being the first to automate data labeling auditing. At its height, the Statehouse Company had more than 30 employees. Now, nine core members of the Cleanlab team are merging into Handshake’s open-source research studio. Cleanlab provides our team with incredible technical know-how. This is because, for the past 30 years, they have concentrated on solving core problems within the data labeling world.
Handshake is now worth $3.3 billion as of 2022. This year, the company expects to be at an annualized revenue run rate of “high hundreds of millions.” By the quarter ending March 2025, projections estimate Handshake will reach an ARR of $300 million. These growth metrics are a testament to Handshake’s pivotal role in the rapidly expanding data labeling universe.
Sahil Bhaiwala, Handshake’s Chief Strategy and Innovation Officer, underscored their commitment to quality in all of their data production. He said that their in-house research team is constantly assessing the flaws in their models. They can guide them in deciding what types of high-quality data should be produced.
“We have an in-house research team that thinks a lot about where our models are weak, what data should we be producing? How high quality is that data?” – Sahil Bhaiwala
Beyond bolstering Handshake’s data labeling expertise, this acquisition will further position Handshake in a highly competitive and burgeoning market. The need for high-quality training data is explosive among AI labs. Handshake’s investments in talent and new technology are sure to prove essential to its future success.
