Developer-focused video platform Mux achieves unicorn status with $105M funding

Barely more than eight months after announcing a $37 million funding round, Mux has another $105 million.

The Series D was led by Coatue and values the company at more than $1 billion (Mux isn’t disclosing the specific valuation). Existing investors Accel, Andreessen Horowitz and Cobalt also participated, as did new investor Dragoneer.

Co-founder and CEO Jon Dahl told me that Mux didn’t need to raise more funding. But after last year’s Series C, the company’s leadership kept in touch with Coatue and other investors who’d expressed interest, and they ultimately decided that more money could help fuel faster growth during “this inflection moment in video.”

Building on the thesis popularized by A16Z co-founder Marc Andreessen, Dahl said, “I think video’s eating software, the same way software was eating the world 10 years ago.” In other words, where video was once something we watched at our desks and on our sofas, it’s now everywhere, whether we’re scrolling through our social media feeds or exercising on our Pelotons.

“We’re at the early days of a five- or 10-year major transition, where video is moving into being a first-class part of every software project,” he said.

Dahl argued that Mux is well-suited for this transition because it’s “a video platform for developers,” with an API-centric approach that results in faster publishing and reliable streaming for viewers. Its first product was a monitoring and analytics tool called Mux Data, followed by its streaming video product Mux Video.

“If you’re going to build a video platform and do it data-first, you need heavy data and monitoring and analytics,” Dahl explained. “We built the data layer [and then] we built the streaming platform.”

Customers include Robinhood, PBS, ViacomCBS, Equinox Media, and VSCO — Dahl said that while Mux works with digital media companies, “our core market is software.” He suggested that back when the company was founded in 2015, video was largely seen as a “niche,” or “something you needed if you were ESPN or Netflix.” But the last few years have illustrated that “video is a fundamental part of how we communicate” and that “every software company should have video as a core part of its products.”

Mux founders Adam Brown, Steven Heffernan, Matt McClure and Jon Dahl

Mux founders Adam Brown, Steven Heffernan, Matt McClure and Jon Dahl

Not surprisingly, demand increased dramatically during the pandemic. During the past year, on-demand streaming via the Mux platform growing by 300%, while live video streaming grew 3700% and revenue quadrupled.

“Which is a lot of work,” Dahl said with a laugh. “We definitely spent a lot of the last year ramping and scaling and investing in the platform.”

This new funding will allow Mux (which has now raised a total of $175 million) to continue that investment. Dahl said he plans to grow the team from 80 to 200 employees and to explore potential acquisitions.

“We were impressed by Mux’s laser focus on the developer community, and saw impressive customer retention and expansion indicative of the strong value their solutions provide,” said Coatue General Partner David Schneider in a statement. “This funding will enable Mux to continue to build on their customer-centric platform and we are proud to partner with Mux as it leads the way to this hybrid future.”


By Anthony Ha

Abacus.AI raises another $22M and launches new AI modules

AI startup RealityEngines.AI changed its name to Abacus.AI in July. At the same time, it announced a $13 million Series A round. Today, only a few months later, it is not changing its name again, but it is announcing a $22 million Series B round, led by Coatue, with Decibel Ventures and Index Partners participating as well. With this, the company, which was co-founded by former AWS and Google exec Bindu Reddy, has now raised a total of $40.3 million.

Abacus co-founder Bindu Reddy, Arvind Sundararajan and Siddartha Naidu. Image Credits: Abacus.AI

In addition to the new funding, Abacus.AI is also launching a new product today, which it calls Abacus.AI Deconstructed. Originally, the idea behind RealityEngines/Abacus.AI was to provide its users with a platform that would simplify building AI models by using AI to automatically train and optimize them. That hasn’t changed, but as it turns out, a lot of (potential) customers had already invested into their own workflows for building and training deep learning models but were looking for help in putting them into production and managing them throughout their lifecycle.

“One of the big pain points [businesses] had was, ‘look, I have data scientists and I have my models that I’ve built in-house. My data scientists have built them on laptops, but I don’t know how to push them to production. I don’t know how to maintain and keep models in production.’ I think pretty much every startup now is thinking of that problem,” Reddy said.

Image Credits: Abacus.AI

Since Abacus.AI had already built those tools anyway, the company decided to now also break its service down into three parts that users can adapt without relying on the full platform. That means you can now bring your model to the service and have the company host and monitor the model for you, for example. The service will manage the model in production and, for example, monitor for model drift.

Another area Abacus.AI has long focused on is model explainability and de-biasing, so it’s making that available as a module as well, as well as its real-time machine learning feature store that helps organizations create, store and share their machine learning features and deploy them into production.

As for the funding, Reddy tells me the company didn’t really have to raise a new round at this point. After the company announced its first round earlier this year, there was quite a lot of interest from others to also invest. “So we decided that we may as well raise the next round because we were seeing adoption, we felt we were ready product-wise. But we didn’t have a large enough sales team. And raising a little early made sense to build up the sales team,” she said.

Reddy also stressed that unlike some of the company’s competitors, Abacus.AI is trying to build a full-stack self-service solution that can essentially compete with the offerings of the big cloud vendors. That — and the engineering talent to build it — doesn’t come cheap.

Image Credits: Abacus.AI

It’s no surprise then that Abacus.AI plans to use the new funding to increase its R&D team, but it will also increase its go-to-market team from two to ten in the coming months. While the company is betting on a self-service model — and is seeing good traction with small- and medium-sized companies — you still need a sales team to work with large enterprises.

Come January, the company also plans to launch support for more languages and more machine vision use cases.

“We are proud to be leading the Series B investment in Abacus.AI, because we think that Abacus.AI’s unique cloud service now makes state-of-the-art AI easily accessible for organizations of all sizes, including start-ups. Abacus.AI’s end-to-end autonomous AI service powered by their Neural Architecture Search invention helps organizations with no ML expertise easily deploy deep learning systems in production.”

 


By Frederic Lardinois