AI startup RealityEngines.AI changed its name to Abacus.AI in July. At the same time, he announced a $ 13 million Series A round. Today, just a few months later, it no longer changes its name, but announces a $ 22 million Series B round, led by Coatue, with the participation of Decibel Ventures and Index Partners. With this, the company, which was co-founded by former AWS and former Google executive Bindu Reddy, has now raised a total of $ 40.3 million.
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 make it easier to build AI models using AI to train and automatically optimize them. That hasn't changed, but as it turns out, many (potential) customers had already invested in their workflows for building and training deep learning models, but were looking for help to put them into production and manage them throughout their lifecycle. .
"One of the big weaknesses [businesses] it was, 'look, I have data scientist and I have my own models that I built in-house. My data scientists built them on laptops, but I don't know how to get them into production. I don't know how to maintain and maintain the models in production. 'I think pretty much every startup is thinking about this problem now, "Reddy said.
Since Abacus.AI had already built those tools anyway, the company decided to split its service into three parts that users can adapt without relying on the full platform. This means that you can now bring your model to the service and ask the company to host and monitor the model for you, for example. The service will manage the model in production and, for example, monitor the model drift.
Another area Abacus.AI has been focusing on for some time is model explainability and de-biasing, so it's making it available as a module as well, as is its real-time machine learning feature store that helps organizations. to create, store and share their machine learning capabilities and deploy them to 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 has been a lot of interest from others to invest as well. "So we decided we could relaunch the next round because we were seeing adoption, we felt ready regarding the product. But we didn't have a large enough sales team. And lifting a little early made sense to build the team. sale, "he said.
Reddy also pointed out that, unlike some of the company's competitors, Abacus.AI is looking to build a full-stack self-service solution that can essentially compete with offerings from large cloud providers. This - and the engineering talent to build it - doesn't come cheap.
It's no surprise then that Abacus.AI plans to use the new funding to grow its R&D team, but will also grow its go-to-market team from two to ten in the coming months. Although the company is betting on a self-service model and has good traction with small and medium-sized businesses, a sales team is still needed to work with large companies.
In January, the company also plans to roll out support for multiple languages and multiple use cases of machine vision.
"We are proud to lead the Series B investment in Abacus.AI, because we believe 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, based on their invention of Neural Architecture Search, helps organizations with no machine learning experience to easily deploy deep learning systems into production.
