Personal blog of Yzmir Ramirez

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,” Yanda Erlich, a p artner at Coatue Ventures  told me. “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.”

RealityEngines.AI, an AI and machine learning startup founded by a number of former Google executives and engineers, is coming out of stealth today and announcing its first set of products.

When the company first announced its $5.25 million seed round last year, CEO Bindu Reddy wasn’t quite ready to disclose RealityEngines’ mission beyond saying that it planned to make machine learning easier for enterprises. With today’s launch, the team is putting this into practice by launching a set of tools that specifically tackle a number of standard enterprise use cases for ML, including user churn predictions, fraud detection, sales lead forecasting, security threat detection and cloud spend optimization. For use cases that don’t fit neatly into these buckets, the service also offers a more general predictive modeling service.

Before co-founding RealiyEngines, Reddy was the head of product for Google Apps and general manager for AI verticals at AWS. Her co-founders are Arvind Sundararajan (formerly at Google and Uber) and Siddartha Naidu (who founded BigQuery at Google). Investors in the company include Eric Schmidt, Ram Shriram, Khosla Ventures and Paul Buchheit.

As Reddy noted, the idea behind this first set of products from RealityEngines is to give businesses an easy entry into machine learning, even if they don’t have data scientists on staff.

Besides talent, another issue that businesses often face is that they don’t always have massive amounts of data to train their networks effectively. That has long been a roadblock for many companies that want to see what AI can do for them but that didn’t have the right resources to do so. RealityEngines overcomes this by creating realistic synthetic data that it can then use to augment a company’s existing data. In its tests, this creates models that are up to 15% more accurate than models that were trained without the synthetic data.

“The most prominent use of generative adversarial networks — GANS — has been to create deepfakes,” said Reddy. “Deepfakes have captured the public’s imagination by highlighting how easy it to spread misinformation with these doctored videos and images. However, GANS can also be applied to productive and good use. They can be used to create synthetic data sets which when then be combined with the original data, to produce robust AI models even when a business doesn’t have much training data.”

RealityEngines currently has about 20 employees, most of whom have a deep background in ML/AI, both as researchers and practitioners.

The vast enterprise tech category is Silicon Valley’s richest, and today it’s poised to change faster than ever before. That’s probably the biggest reason to come to TechCrunch’s first-ever show focused entirely on enterprise. But here are five more reasons to commit to joining TechCrunch’s editors on September 5 at San Francisco’s Yerba Buena Center for an outstanding day (agenda here) addressing the tech tsunami sweeping through enterprise. 

No. 1: Artificial intelligence
At once the most consequential and most hyped technology, no one doubts that AI will change business software and increase productivity like few, if any, technologies before it. To peek ahead into that future, TechCrunch will interview Andrew Ng, arguably the world’s most experienced AI practitioner at huge companies (Baidu, Google) as well as at startups. AI will be a theme across every session, but we’ll address it again head-on in a panel with investor Jocelyn Goldfein (Zetta), founder Bindu Reddy (Reality Engines) and executive John Ball (Salesforce / Einstein). 

No. 2: Data, the cloud and Kubernetes
If AI is at the dawn of tomorrow, cloud transformation is the high noon of today. Indeed, 90% of the world’s data was created in the past two years, and no enterprise can keep its data hoard on-prem forever. Azure’s CTO Mark Russinovitch will discuss Microsft’s vision for the cloud. Leaders in the open-source Kubernetes revolution — Joe Beda (VMware), Aparna Sinha (Google) and others — will dig into what Kubernetes means to companies making the move to cloud. And last, there is the question of how to find signal in all the data — which will bring three visionary founders to the stage: Benoit Dageville (Snowflake), Ali Ghodsi (Databricks) and Murli Thirumale (Portworx). 

No. 3: Everything else on the main stage!
Let’s start with a fireside chat with SAP CEO Bill McDermott and Qualtrics Chief Experience Officer Julie Larson-Green. We have top investors talking where they are making their bets, and security experts talking data and privacy. And then there is quantum computing, the technology revolution waiting on the other side of AI: Jay Gambetta, the principal theoretical scientist behind IBM’s quantum computing effort, Jim Clarke, the director of quantum hardware at Intel Labs and Krysta Svore, who leads Microsoft’s quantum effort.

All told, there are 21 programming sessions.

No. 4: Network and get your questions answered
There will be two Q&A breakout sessions with top enterprise investors; this is for founders (and anyone else) to query investors directly. Plus, TechCrunch’s unbeatable CrunchMatch app makes it really easy to set up meetings with the other attendees, an incredible array of folks, plus the 20 early-stage startups exhibiting on the expo floor.

No. 5: SAP
Enterprise giant SAP is our sponsor for the show, and they are not only bringing a squad of top executives, they are producing four parallel track sessions, featuring key SAP Chief Innovation Officer Max Wessel, SAP Chief Designer and Futurist Martin Wezowski and SAP.IO’s managing director Ram Jambunathan (SAP.iO), in sessions including how to scale-up an enterprise startup, how startups win large enterprise customers, and what the enterprise future looks like.

Check out the complete agenda. Don’t miss this show! This line-up is a view into the future like none other. 

Grab your $349 tickets today, and don’t wait til the day of to book because prices go up at the door!

We still have two Startup Demo Tables left. Each table comes with four tickets and a prime location to demo your startup on the expo floor. Book your demo table now before they’re all gone!

Synchronize your Fitbits, people. You have 72 hours left to get your fiscal fitness on. Three days to save $100 on tickets to TC Sessions: Enterprise 2019 in San Francisco on September 5. Buy your early-bird ticket by August 9 at 11:59 p.m. (PT) and then go back to counting your steps.

We say with confidence that no tech category’s more competitive than enterprise software. The gigantic, $500 billion market generates a constant flow of multibillion-dollar acquisitions every year. And it takes a special kind of fierce early-stage enterprise startup to jump in, invent new services and shake up old-school incumbents.

More than 1,000 attendees will be in the house to explore this rich, complex topic, TechCrunch-style. Our editors will interview top titans in the enterprise world — like SAP CEO, Bill McDermott; Atlassian co-founder, Scott Farquhar; and Jocelyn Goldfein, managing director at Zetta Venture Partners. They’ll also tap rising founders of upstart startups.

The enterprise just can’t get enough of AI, but large companies face a huge challenge: packaging all that data in machine learning models — a necessary element for using AI to automate processes. That’s why we’re especially excited that Bindu Reddy, co-founder and CEO at RealityEngines, will join us onstage.

Her company aims to create research-driven cloud services to reduce some of the inherent complexity of working with AI tools. Reddy, along with investor Jocelyn Goldfein, a managing director at Zetta Venture Partners, and others will talk about the growing role of AI in the enterprise.

That’s just the tip of the Enterprise iceberg. More than 20 interviews, panel discussions, Q&As and breakout sessions will cover a wide range of technologies, including intelligent marketing automation, the cloud, Kubernetes and even quantum and blockchain. Peruse the agenda to see what else we have in store for you.

Early-bird pricing for TC Sessions: Enterprise 2019 ends in just 72 hours. Buy your ticket by August 9 at 11:59 p.m. (PT) and you’ll save $100. But wait, there’s more — for every ticket you buy, we’ll register you for a free Expo-only pass to TechCrunch Disrupt SF 2019. Now that’s fiscal fitness.

Is your company interested in sponsoring or exhibiting at TC Sessions: Enterprise? Contact our sponsorship sales team by filling out this form.

There is surely no shortage of data in the modern enterprise, and data is the fuel for AI. Yet packaging that data in machine learning models remains a huge challenge for large companies. Without that capability, automating processes with AI underpinnings remains elusive for many companies.

RealityEngines wants to change that by creating research-driven cloud services that can reduce some of the inherent complexity of working with AI tools. We are excited to be including Bindu Reddy, co-founder and CEO at RealityEngines, at TechCrunch Sessions: Enterprise, taking place in San Francisco on September 5.

Reddy will be joining investor Jocelyn Goldfein, a managing director at Zetta Venture Partners, and others. They will be discussing with TechCrunch editors the growing role of AI in the enterprise, as companies try to take advantage of the capabilities machines have over humans to process large amounts of information quickly.

She knows from whence she speaks. Before founding RealityEngines, Reddy helped launch AI Verticals at AWS where she served as general manager. She was responsible for bringing to market Amazon Personalize and Amazon Forecast, two tools that help organizations create machine learning models.

Before that, she was CEO and co-founder at yet another AI startup called Post Intelligence, a company that purported to help social media influencers write AI-driven tweets. She later sold that company to Uber. If that isn’t enough for you, she served as head of Products for Google Apps, where she was in charge of Docs, Sheets, Slides, Sites and Blogger.

Early-bird tickets to see Bindu and our lineup of enterprise influencers at TC Sessions: Enterprise are on sale for just $249 when you book here; but hurry, prices go up by $100 soon! Students, grab your discounted tickets for just $75 here.

Artificial intelligence is quickly becoming a foundational technology for enterprise software development and startups have begun addressing a variety of issues around using AI to make software and processes much more efficient.

To that end, we are delighted to announce that Jocelyn Goldfein, a Managing Director at Zetta Venture Partners will be joining on us a panel to discuss AI in the enterprise. It will take place at the TechCrunch Sessions: Enterprise show on September 5 at the Yerba Buena Center in San Francisco.

It’s not just startups that are involved in AI in the enterprise. Some of the biggest names in enterprise software including Salesforce Einstein, Adobe Sensei and IBM Watson have been addressing the need for AI to help solve the enterprise data glut.

Computers can process large amounts of information much more quickly than humans, and as enterprise companies generate increasing amounts of data, they need help understanding it all as the volume of information exceeds human capacity to sort through it.

Goldfein brings a deep engineering background to her investment work. She served as a VP of engineering at VMware and as an engineering director at Facebook, where she led the project that adopted machine learning for the News Feed ranker, launched major updates in photos and search, and helped spearhead Facebook’s pivot to mobile. Goldfein drove significant reforms in Facebook hiring practices and is a prominent evangelist for women in computer science. As an investor, she primarily is focused on startups using AI to take more efficient approaches to infrastructure, security, supply chains and worker productivity.

At TC Sessions: Enterprise, she’ll be joining Bindu Reddy from Reality Engines along with other panelists to discuss the growing role of AI in enterprise software with TechCrunch editors. You’ll learn why AI startups are attracting investor attention and how AI in general could fundamentally transform enterprise software.

Prior to joining Zetta, Goldfein had stints at Facebook and VMware, as well as startups Datify, MessageOne and Trilogy/pcOrder.

Early Bird tickets to see Joyce at TC Sessions: Enterprise are on sale for just $249 when you book here; but hurry, prices go up by $100 soon! Students, grab your discounted tickets for just $75 here.

RealityEngines.AI, a research startup that wants to help enterprises make better use of AI, even when they only have incomplete data, today announced that it has raised a $5.25 million seed funding round. The round was led by former Google CEO and Chairman Eric Schmidt and Google founding board member Ram Shriram. Khosla Ventures, Paul Buchheit, Deepchand Nishar, Elad Gil, Keval Desai, Don Burnette and others also participated in this round.

The fact that the service was able to raise from this rather prominent group of investors clearly shows that its overall thesis resonates. The company, which doesn’t have a product yet, tells me that it specifically wants to help enterprises make better use of the smaller and noisier data sets they have and provide them with state-of-the-art machine learning and AI systems that they can quickly take into production. It also aims to provide its customers with systems that can explain their predictions and are free of various forms of bias, something that’s hard to do when the system is essentially a black box.

As RealityEngines CEO Bindu Reddy, who was previously the head of products for Google Apps, told me, the company plans to use the funding to build out its research and development team. The company, after all, is tackling some of the most fundamental and hardest problems in machine learning right now — and that costs money. Some, like working with smaller data sets, already have some available solutions like generative adversarial networks that can augment existing data sets and that RealityEngines expects to innovate on.

Reddy is also betting on reinforcement learning as one of the core machine learning techniques for the platform.

Once it has its product in place, the plan is to make it available as a pay-as-you-go managed service that will make machine learning more accessible to large enterprise, but also to small and medium businesses, which also increasingly need access to these tools to remain competitive.