Talla Sells Virtual Assistants for the Workplace as A.I. Startups Focus

Xconomy Boston — 

Slowly but surely, artificial intelligence is creeping into everyday life. Think of all the questions Siri and Cortana can answer; or e-mail programs that schedule appointments; or Facebook’s M service that aims to do things like make purchases and book travel arrangements on your behalf.

After decades of research on A.I. technologies, companies of all sizes are looking to cash in on the promise of virtual digital assistants—software “bots” that can interact with you, automatically handle certain tasks, and even make decisions for you. That last bit might concern you—as it should—but the tradeoff is having more time to spend on things that are important (or interesting). That’s the idea, anyway.

It’s just one piece of the overall A.I. puzzle—but it’s a potentially lucrative one. Virtual assistants sit at the intersection of business and technology areas like machine learning, natural language processing, mobile interfaces, and big-data analytics. Companies that figure out how to apply advances in these fields to assist people via e-mail, social media, or other platforms stand to gain plenty of users, clout, and revenue.

One new company in the field, Cambridge, MA-based Talla, is talking about its approach after half a year in stealth mode. The startup’s experience and prospects speak to how the landscape for A.I. companies may play out.

Talla is rumored to be raising a seed round in the neighborhood of $3.5 million, but the company declined to comment on that. It previously raised a $600,000 angel round last year from investors including Converge Venture Partners.

Talla’s founder and CEO is Rob May, the founder and former CEO of Backupify, a data-protection company that was acquired by Datto in late 2014. (May left Datto last June.) His co-founder and chief data scientist is Byron Galbraith, a recent Boston University PhD in cognitive and neural systems who has worked in software development and brain-machine interfaces. The two (pictured above) started collaborating on Talla last fall, May says, after meeting through Neurala CEO Max Versace.

May says the startup began with a couple of tenets: over the next decade, he predicts, “every knowledge worker will have a virtual assistant to help them do their job.” And, he says, “text will be the primary way we communicate with them.”

The first step, then, was figuring out which type of market to go after. “If you’re doing A.I., you have to think about how you’re going to compete with Google, Facebook, and Amazon,” May says. It’s important to “not rely on public datasets where those guys can beat you,” he adds.

That led Talla to look at internal corporate data and to try to “build a knowledge graph of what’s known in a company,” May says. The team set out to build A.I.-based software that integrates with messaging apps Slack and HipChat. These communication tools have gained traction with startups, media companies, and big tech firms as alternatives to e-mail. (Speaking of e-mail, other companies such as Mimecast are also working on managing knowledge across workforces.)

The virtual assistant that first resonated with beta users, May says, is one for handling recruiting and human resources tasks. The Talla bot interacts with a user via text on a smartphone (see screenshot below). It can do things like create a dossier on a job candidate, suggest interview questions to ask, and find similar candidates on LinkedIn. It can also manage tasks such as compiling interview notes from different people in a company, or responding to basic requests for information from candidates.

Talla screenshot of recruiting bot

Talla can also answer simple HR questions from employees, such as, “What’s my co-pay for a dental visit?” The bot knows to ask, for example, whether it’s a routine cleaning appointment or something else, and adjust its answer accordingly, May says.

Under the hood, he says, Talla uses natural language processing techniques including word vectors (modeling how a word relates to others), and some deep learning (multi-layer neural networks that find patterns in large datasets). … Next Page »

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