Personal blog of Yzmir Ramirez

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.

Google and its flagship search portal opened the door to the possibilities of how to build a business empire on the back of organising and navigating the world’s information, as found on the internet. Now, a startup that’s built a search engine tailored to the needs of enterprises and their own quests for information has raised a round of funding to see if it can do the same for the B2B world.

AlphaSense, which provides a way for companies to quickly amass market intelligence around specific trends, industries and more to help them make business decisions, has closed a $50 million round of funding, a Series B that it’s planning to use to continue enhancing its product and expanding to more verticals.

The company counts some 1,000 clients on its books, with a heavy emphasis on investment banks and related financial services companies. That’s in part because of how the company got its start: Finnish co-founder and CEO Jaakko (Jack) Kokko had been an analyst at Morgan Stanley in a past life and understood the labor and time pain points of doing market research, and decided to build a platform to help shorten a good part of the information-gathering process.

“My experience as an analyst on Wall Street showed me just how fragmented information really was,” he said in an interview, citing as one example how complex sites like those of the FDA are not easy to navigate to look for new information and updates — the kind of thing that a computer would be much more adept at monitoring and flagging. “Even with the best tools and services, it still was really hard to manually get the work done, in part because of market volatility and the many factors that cause it. We can now do that with orders of magnitude more efficiency. Firms can now gather information in minutes that would have taken an hour. AlphaSense does the work of the best single analyst, or even a team of them.”

(Indeed, the “alpha” of AlphaSense appears to be a reference to finance: it’s a term that refers to the ability of a trader or portfolio manager to beat the typical market return.)

The lead investor in this round is very notable and says something about the company’s ambitions. It’s Innovation Endeavors, the VC firm backed by Eric Schmidt, who had been the CEO of none other than Google (the pace-setter and pioneer of the search-as-business model) for a decade, and then stayed on as chairman and ultimately board member of Google and then Alphabet (its later holding company) until just last June.

Schmidt presided over Google at what you could argue was its most important time, gaining speed and scale and transitioning from an academic idea into a full-fledged, huge public business whose flagship product has now entered the lexicon as a verb and (through search and other services like Android and YouTube) is a mainstay of how the vast majority of the world uses the web today. As such, he is good at spotting opportunities and gaps in the market, and while enterprise-based needs will never be as prominent as those of mass-market consumers, they can be just as lucrative.

“Information is the currency of business today, but data is overwhelming and fragmented, making it difficult for business professionals to find the right insights to drive key business decisions,” he said in a statement. “We were impressed by the way AlphaSense solves this with its AI and search technology, allowing businesses to proceed with the confidence that they have the right information driving their strategy.”

This brings the total raised by AlphaSense to $90 million, with other investors in this round including Soros Fund Management LLC and other unnamed existing investors. Previous backers had included Tom Glocer (the former Reuters CEO who himself is working on his own fintech startup, a security firm called BlueVoyant), the MassChallenge incubator, Tribeca Venture Partners and others. Kokko said AlphaSense is not disclosing its valuation at this point. (I’m guessing though that it’s definitely on the up.)

There have been others that have worked to try to tackle the idea of providing more targeted, and business-focused, search portals, from the likes of Wolfram Alpha (another alpha!) through to Lexis Nexis and others like Bloomberg’s terminals, FactSet, Business Quant and many more.

One interesting aspect of AlphaSense is how it’s both focused on pulling in requests as well as set up to push information to its users based on previous search parameters. Currently these are set up to only provide information, but over time, there is a clear opportunity to build services to let the engines take on some of the actions based on that information, such as adjusting asking prices for sales and other transactions.

“There are all kinds of things we could do,” said Kokko. “This is a massive untapped opportunity. But we’re not taking the human out of the loop, ever. Humans are the right ones to be making final decisions, and we’re just about helping them make those faster.”

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.

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