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A top VC firm is investing $8 million in a startup that's helping lawyers win more cases, faster

A top VC firm is investing $8 million in a startup that's helping lawyers win more cases, faster
Tech3 min read

aj shankar everlaw

Everlaw

Everlaw CEO and founder AJ Shankar

In the late 2000's, AJ Shankar was a grad student in UC Berkeley's computer science department when a local law by firm came in looking for a technical expert on a case.

It led Shankar to stay on as a moonlighting consultant with the law firm while he finished his degree.

And in 2010, he took everything he learned at the law firm and founded his startup Everlaw.

Today, Everlaw announces an $8.1 million round of funding from high-profile VC firm Andreessen Horowitz, with ex-Microsoft Windows boss Steven Sinofsky joining the company's board.

Everlaw is a startup that uses artificial intelligence to help lawyers quickly and easily sift through the "couple million documents" of emails, reports, and presentations that winning a big case can require, as Shankar describes it.

"The volume of data is insane, and only getting bigger," says Shankar.

Discovery

The technical term for what Everlaw does is "eDiscovery," and it's a big deal, as law firms either task paralegals to go through those documents by hand, or else use business software from HP Autonomy and other firms.

If you've seen the end of the second season of Silicon Valley, where startup Pied Piper gets buried under dozens of boxes of printed documents by archnemesis Hooli in an attempt to handicap their legal defense, you can guess why eDiscovery is so necessary.

Right now, Everlaw is being used by lawyers in the litigation over the General Motors faulty ignition switch recall. And it's going to use that Andreesen Horowitz cash to keep improving its technology and marketing both in an effort to keep landing big cases.

GM ignition recall

REUTERS/John Gress

A recalled Chevy Cobalt ignition switch is seen at Raymond Chevrolet in Antioch, Illinois, July 17, 2014.

The overall legal market is an attractive opportunity for tech companies. Law is a $400 billion industry in the US alone, according to some estimates.

And eDiscovery can account for as much as 70% of the cost of any legal action or lawsuit - for a lawsuit that costs a litigant $2.5 million, as much as $1.75 million of that can go toward discovery. Law firms often spend as much as $100,000 a month on eDiscovery, and one analyst in 2012 found the average cost was about $18,000 per gigabyte.

Plus, those existing solutions are often based on aging, creaky software, Shankar says.

But Everlaw charges a comparatively straightforward price per gigabyte of documents stored and scanned. It simplifies pricing for customers, Shankar says, while also generally reducing their costs.

Human After All

Another huge edge, Shankar says, is Everlaw's design and speed.

In a recent $450 million class action case, Shankar says, a law firm tried out Everlaw versus their usual go-to solution - and saved 700 manhours of search.

"People are desperate for it and will pay for it," Shankar says.

But it's the technology under the hood that makes Everlaw so useful to lawyers who want to move faster, Shankhar says.

"We actually bring to bear really sophisticated artificial intelligence," he says.

everlaw screenshot

Everlaw

Everlaw screenshot

Once you're up and running with the Everlaw software, it starts to notice which documents you're bothering to open, which ones you're spending time on, and which you're sharing. From there, it can suggest which document you might like to to look at next, and the next one, and the next one.

It means that in all those mountains of data, a lawyer is much more likely to have just the file they need.

"Fewer things fall through the cracks," Shankar says.

Still, Shankar doesn't exactly think Everlaw will replace the need for human lawyers anytime soon: When a case can hinge on a judge's interpretation of one sentence of one e-mail, machines just don't have the capacity to understand the right level of nuance.

"As a computer scientist, where we are now, we're not even close," Shankar says.

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