Tecton.ai emerged hidden with a $ 20 million Series A to build a machine learning platform

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Three former Uber Engineers who helped build the company’s Michelangelo machine learning platform left the company last year to launch Tecton.ai and create an operational machine learning platform for everyone else. Today, the company announced a $ 20 million Series A from some high profile investors.

Andreessen Horowitz and Sequoia Capital led the round with Martin Casado, general partner at a16z, and Matt Miller, partner at Sequoia, who joined the company’s board of directors in accordance with the terms of the agreement. Today’s investment in combination with the seeds they used to build the product last year is $ 25 million. Not bad in today’s environment.

However, if you have the pedigree of these three founders – CEO Mike Del Balso, CTO Kevin Stumpf and VP of Engineering Jeremy Hermann – who have all contributed to building the Uber system, investors will be spending some money, especially if you try a difficult one Learning to solve problem around the machine.

The Michelangelo system was Uber’s machine learning platform, which looked at, among other things, driver safety, estimated time of arrival and fraud detection. The three founders wanted to use what they learned at Uber for companies struggling with machine learning.

“Tecton is really about helping companies to easily create machine learning systems at the production level, put them into production and operate them properly. And we’re focusing on the machine learning data layer, ”CEO Del Balso told TechCrunch.

Credit: Tecton.ai

According to Del Balso, part of the problem, even for companies familiar with machine learning, is creating and reusing models for different use cases. In fact, the vast majority of machine learning projects fail, and Tecton wanted to give these companies the tools to change this.

The company has developed a solution that makes it much easier to build a model and get it up and running by connecting to data sources, making it easier to reuse the data and models in related use cases. “We are focusing on data learning related to machine learning and all data pipelines related to powering these models,” said Del Balso.

Martin Casado of a16z certainly sees a problem in finding a solution and he likes the background of this team and his understanding of how to build such a system on a large scale. “After following a series of intense engagements with top ML teams and their interest in what Tecton built, we invested in Tectons A alongside Sequoia. We are firmly convinced that these systems will continue to be based on data and ML models and that a completely new tool chain is required to develop them further, ”he wrote in a blog post in which the funding was announced.

The company currently has 17 employees and is looking for employees, particularly data scientists and machine learning engineers, with a target of 30 employees by the end of the year.

Del Balso is certainly aware of the current economic situation, but believes he can still build this company because it solves a problem where people are really looking for machine learning help right now.

“The customers we speak to have to solve these problems and we don’t see any slowdown,” he said.

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