Brian Rieger (the president of Labelbox) and Manu Sharma, the CEO, met while attending college at Embry-Riddle Aeronautical University, Florida.
Data annotation company Labelbox received offers from investors to accept ever larger sums of money, despite the flurry of funding for data startups. One venture capitalist offered his leadership on the $200 million investment. It partnered with SoftBank, a well-known writer of large checks, but decided to only take about half the capital.
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Data Startup Labelbox Reaches $1 Billion Value With SoftBank Funding
Labelbox announced that it had closed a $110million Series D funding round led by SoftBank’s Vision Fund II. Two strategic investors were added to Labelbox’s portfolio: Snowpoint Ventures to assist it in selling to the government and Databricks Ventures to strengthen its partnership with the high-flying data management company, which is widely expected to go public this year.
Andreessen Horowitz, Eduardo Saverin from B Capital Group, and the Ark Invest asset manager Cathie wood made follow-on investments. Robert Kaplan from SoftBank, who first invested in Labelbox at B Capital, joined the board as an observer. Manu Sharma, the CEO and co-founder of Labelbox declined to reveal a precise valuation but stated that Labelbox was now “basically a unicorn” thanks to the new funding. This puts it on the brink of $1 billion.
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Labelbox was founded in 2018 by Sharma and Brian Rieger, with Dan Rasmuson, who is no longer with Labelbox. It is trying to be a leader among its peers, many of which were established years ago and have become unicorns. Sharma and Rieger met while studying aerospace engineering at Embry-Riddle Aeronautical University. This school is located one hour from Cape Canaveral, which is known for producing many of America’s top pilots.
After graduating, the two aviation enthusiasts tried their hand at starting a space hardware business. However, it failed. Both started new jobs in 2017 that utilized artificial intelligence to process data more efficiently. “We were only there briefly because we realized that there was an entirely new paradigm [for AI],” Sharma said all the lessons they taught him from school are still relevant. Sharma recently moved with Rieger to Miami’s outskirts. This was more for aviation than the web3 scene.
Labelbox, true to its name, is developing for the data labeling portion of the machine-learning process. This allows smaller batches of “training” data to be annotated to allow AI models to learn how to make predictions from large amounts of raw data. Other well-funded startups that offer data labeling solutions include Scale AI (a $7.3 billion valuation), which announced last October it had achieved $100 million in annual recurring revenue.
The snorkel also has a $1 billion valuation. Sharma claims that Labelbox has been the most popular startup among enterprise customers over the past 18 months. “When we talk to the enterprise, we don’t see the companies you may consider our competitors.” He says Labelbox is competing with Amazon SageMaker and other in-house solutions large companies are developing. Sharma wasn’t open to discussing Labelbox’s revenue but said the company has 200 customers with a better retention rate than 150%.
He says, “We sell to large organizations with multiple AI use cases.” Allstate Auto Insurance used Labelbox to create models that could identify certain characteristics in an image of an insurance claim. This includes license plates and the type of vehicular damage. Sharma claims that the company was able to move from the idea stage to the implementation of the AI model in just two weeks. NASA’s Jet Propulsion Lab uses Labelbox to label videos showing molecules’ motion on earth. This allows them to train various algorithms to search for life-like movements in space.
Sharma stated that the new capital injection, which exceeds the previous rounds’ $79 million total, will accelerate Labelbox’s product development for enterprise customers. The company’s emphasis on software tools that improve data quality rather than code makes it different in its development. Andrew Ferguson, vice president of corporate development and ventures at Databricks, stated that Labelbox was chosen by his company to deepen its partnership due to its tech-oriented approach. “While this approach is valid, and some companies use it, it’s less scalable than a technology-driven approach.
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This is why Labelbox chose SoftBank to lead its investment in this round. Sharma recalls a conversation she had with Masayoshi, son, as “one of our best conversations” with a VC. Labelbox president and cofounder Rieger says there is a tendency to focus on the “here and now” in typical venture capital engagements. Because Son was focused on the long-term goals of SoftBank, it was an “aha” moment when he spoke with SoftBank.
“When you look at that frame, the questions transform significantly into larger fundamental questions such as, ‘How will it unfold?’ or? What control points are there?'” Rieger pointed out future AI developments that Labelbox is interested in, such as processing “an unprecedented amount of information” using 4K video data.
Labelbox plans to use the contracts it has signed with the Department of Defense for distribution to expand into the government sector. Snowpoint Ventures’ cofounder Doug Philippone says that Palantir is focusing on the problem I identified as the most urgent. “In the absence of a Labelbox-type platform, they have what they refer to as ‘labeling skimps.'” His new company contributed 20% to Labelbox’s capital on the strength of Labelbox’s opportunity.
It has legitimate revenue and growth but almost no government business. He says that the government faces the most complex problems regarding data size and scale. This stuff must work because it is vital for our country’s survival.