All posts in “Events”

Meetup + Pitch-Off: London 2017

Matt Mitchell of CryptoHarlem is building an open source tool to help organizations prepare for data breaches

14 minutes ago by John Mannes

Pinterest raises $150M at a $12.3B valuation as it makes a full press into visual search

16 minutes ago by Matthew Lynley

Tulip, the app platform for manufacturers, picks up $13 million from NEA

57 minutes ago by Jordan Crook

Take a look at these first pictures of Fisker’s $130K EMotion electric car

1 hour ago by Darrell Etherington

iOS 11 will help you free up storage on your iPhone through personalized suggestions

1 hour ago by Sarah Perez

Facebook Live gets accessible with third-party closed captioning

1 hour ago by Josh Constine

Autopilot raises $12 million to help businesses with targeted client emails

1 hour ago by Katie Roof

Uber has fired more than 20 people over harassment probe

1 hour ago by Sarah Buhr

VR is in Apple’s future, but AR is the logical short term play

3 hours ago by Brian Heater

WhatsApp embraces visuals with filters, albums, and reply shortcuts

3 hours ago by Josh Constine

TechCrunch Startup Battlefield Africa

Spotify buys AI startup Niland to develop its music personalization and recommendations

4 hours ago by Jon Russell

Sennheiser’s PC 373D Dolby 7.1 gaming headphones sound best with it disabled

5 hours ago by Stefan Etienne

Restaurant guide Zomato got off lightly after a hacker grabbed 6.6M user passwords

5 hours ago by Jon Russell

In the car with Android in the Car

5 hours ago by Darrell Etherington

Kickstarter launches tools for creators, because hardware is hard

5 hours ago by Brian Heater

Telegram now lets users buy things from chatbots in its messaging app

5 hours ago by Jon Russell

ATAP goes AWOL at Google I/O

6 hours ago by Frederic Lardinois

Twitter hires a new GM of revenue products

6 hours ago by Matthew Lynley

Profiting socially on nickels and dimes

7 hours ago by Patrick Wallen

Facebook and MLB partner to bring live-streamed games to the social network

8 hours ago by Sarah Perez

Leverage is building a project management application with outsourced virtual assistance built in


Using outsourced help – whether that’s using a virtual assistant to help you book travel or hiring a development firm to build your website – is something that nearly all businesses need from time to time. But finding a qualified person to do that job from freelance job boards on online recommendations can be difficult. A company called Leverage wants to make using virtual assistance easier for individuals, small businesses and larger organizations by offering an on-demand workforce that can do just about anything.

The way co-founder Ari Meisel described Leverage’s value proposition is that it “can do anything that’s legal for anyone or any business.”

This includes things like personal shopping or travel planning for overwhelmed and very busy working professionals, as well as business needs like graphic design, building websites or apps, producing podcasts, crafting a sales funnel, and more.

The idea for Leverage begin, as many companies do, with a personal struggle. Nine years ago, Meisel was diagnosed with Crohn’s Disease, and found he needed to reduce his own stress levels by slowing down how much he was doing – leading to a need for outsourced help.

When he met friend and co-founder Nick Sonnenberg, who then happened to be working on his own productivity app at the time, the startup idea was born.

The two founders launched Leverage the day after the shutdown of a notable name in the virtual assistance market, Zirtual. Immediately, they had 10 clients from a Mastermind coaching group Meisel was running.

What makes Leverage different from hiring a virtual assistant on your own is not just the quality and expertise of the team members it offers.

“You don’t just get an individual assistant, you get the whole team,” explains Meisel. “We provide the personalization of the individual assistant with the expertise and the bandwidth of the whole team.”

By their first full year of business, Leverage had grown its revenue to $1 million, and is on track for $4 million this year. It now has a client base of around 450 customers who range from busy individuals and small businesses to large companies and organizations that have as much as $100 million in revenue per year.

Its customer base today includes a number of notable names, including Shark Tank’s Daymond John, NYT bestselling author Sally Hogshead, marketing guru Joe Polish, Gazelles Inc. founder and CEO Verne Harnish, and others. It also has a number of business customers, including some government agencies.

  1. tcdisrupt-ny17-9363

    Leverage presents at Startup Battlefield at TechCrunch Disrupt NY 2017

  2. tcdisrupt-ny17-9365

    Leverage presents at Startup Battlefield at TechCrunch Disrupt NY 2017

  3. tcdisrupt-ny17-9392

    Leverage presents at Startup Battlefield at TechCrunch Disrupt NY 2017

  4. tcdisrupt-ny17-9371

    Leverage presents at Startup Battlefield at TechCrunch Disrupt NY 2017

  5. tcdisrupt-ny17-9375

    Leverage presents at Startup Battlefield at TechCrunch Disrupt NY 2017

  6. tcdisrupt-ny17-9376

    Leverage presents at Startup Battlefield at TechCrunch Disrupt NY 2017

  7. tcdisrupt-ny17-9384

    Leverage presents at Startup Battlefield at TechCrunch Disrupt NY 2017

  8. tcdisrupt-ny17-9389

    Leverage presents at Startup Battlefield at TechCrunch Disrupt NY 2017

  9. tcdisrupt-ny17-9362

    Leverage presents at Startup Battlefield at TechCrunch Disrupt NY 2017

To use Leverage, businesses pay $199 per month for a subscription and then another $40 per hour, which is billed by the second. The subscription includes unlimited (unbillable) coaching, as well. This makes Leverage not just another outsourced workforce option but also a business consulting service, Meisel says.

In addition, members gain access to a Slack community of around 500 members which focuses on the topic of increasing productivity.

The company went on stage this afternoon at TechCrunch Disrupt NY 2017 (where it won the Wild Card spot to compete in the Startup Battlefield) to preview its own product management software, Leverage Dashbrd. The application will be free to use, but will have the ability to instantly outsource tasks to its workforce with the touch of a button.

Leverage has been profitable from day one, the founders claim, and has never raised outside funding.

Deep Science AI monitors security feeds for masks and guns to quicken response times


You’re working late at the 7-Eleven when a masked man comes through the door with a gun. You raise your hands, follow his instructions, empty the cash register and throw some burners in the bag. As he runs out the door, you note his height, collect yourself and call 9-1-1. Unless you don’t need to because the mask immediately tipped off your store’s AI, and the police are already on their way with a description. That’s what Startup Battlefield company Deep Science AI hopes to enable.

There are security cameras everywhere, founders Sean Huver and Sam Tkach thought, and deep learning models are getting really good at spotting individual objects in footage — for example, masks and guns. So why not put the two together?

“People find it surprising how prevalent this problem is in high-crime areas,” CEO Sean Huver told TechCrunch. “There are 200 robberies like this a day on average, so around 75,000 per year.”

  1. tcdisrupt-ny17-9254

    Deep Science AI presents at Startup Battlefield at TechCrunch Disrupt NY 2017

  2. tcdisrupt-ny17-9259

    Deep Science AI presents at Startup Battlefield at TechCrunch Disrupt NY 2017

  3. tcdisrupt-ny17-9261

    Deep Science AI presents at Startup Battlefield at TechCrunch Disrupt NY 2017

  4. Deep Science AI

    Deep Science AI presents at Startup Battlefield at TechCrunch Disrupt NY 2017

  5. tcdisrupt-ny17-9275

    Deep Science AI presents at Startup Battlefield at TechCrunch Disrupt NY 2017

  6. tcdisrupt-ny17-9273

    Deep Science AI presents at Startup Battlefield at TechCrunch Disrupt NY 2017

  7. tcdisrupt-ny17-9269

    Deep Science AI presents at Startup Battlefield at TechCrunch Disrupt NY 2017

That makes it a very clear threat for thousands of franchise and mom-‘n-pop bodegas and gas stations throughout the country. But such robberies often go unpunished because they’re generally only reported after the perpetrator has fled, unless someone is always watching the security cam — a costly service.

Deep Science AI is totally bootstrapped and has a straightforward mission: use the tireless analysis capability of AIs to augment human oversight to provide a cheaper and maybe even better way to keep an eye on your store.

“We’re the first to build a whole platform that can scale up to thousands of cameras, and the first to do a real-world deployment,” Huver said. And at around $2 per camera per day, it’s about 1/10th the price of hiring a human to watch your feeds for you.

A great deal of security cameras are IP-based, sending their footage to some data center to be archived or, if they pay for it, monitored. Deep Science’s system sits on that stream and runs it through a set of neural networks trained on thousands of hours of real robberies — and a few fake ones.

“Obviously you want the data to be as close to the real thing as possible,” Huver said, “but we needed to get some angles that we didn’t see, so we also filmed quite a bit on our own. We have a whole collection of masks and fake guns.”

The resulting systems do pretty well down to about 30 “pixels on target,” meaning that the gun or face is most confidently detected when it’s that many pixels across in the footage. If one network isn’t quite sure whether something is a gun, the imagery gets sent to a “binary specialist” network that gives a second opinion.

If it looks bad enough, it goes to a human, as an alert in a Slack channel, who can alert the authorities. (If no one responds within a few seconds, it goes to a backup human.)

“We’re at the point where one analyst can deal with about 500 cameras, and they deal with one false positive every 40 seconds or so,” Huver explained. They hope to get that number up to around 800 or 1,000 as the networks improve and the false positive rate drops.

But the company is confident that the system in its current state is more than good enough to deploy. In fact, it’s already deployed in a limited way.

It’s been running in a closed beta for four weeks at 18 locations, which has helped improve their algorithms, and they launched an open beta onstage today, which should expand this to 200 locations.

Sunoco, which runs more than a few gas stations, has expressed interest in joining; large companies like that, you may think, can afford the nicer service. True, but this is cheaper at scale and may prove to be as effective as human monitors. And anything companies can do to improve security and lower their liability is actively pursued — poor security practices tend to leave them open to lawsuits.

Deep Science does have to pay its humans, even if there aren’t many of them, and to that end it is both looking to grow organically and to solicit funding. A member of its board hails from venerable security company ADT, and it may be possible to get into the system of security middlemen who equip and plan deployments for locations. This system would be an upsell, but a cheaper one than 24/7 human monitoring.

Detecting masks and guns is a sort of minimum viable product, but the company doesn’t intend to stop there. Once they’re in the system, there are all kinds of interesting data that can be extracted. Perhaps there’s no gun or mask, but an employee puts their hands in the air. Or maybe a window is broken when no one is around. Or maybe a fire starts, and can be responded to even before the smoke detectors go off.

These and other features will be part of the open beta, so if you’re a small business and this whole AI monitoring thing doesn’t freak you out, head over here to sign up.