These Three Young Startups Show Incredible Promise
A machine learning technology that reads scientific papers, a multi-channel messaging platform and a customer support platform for high-growth companies are among the finalists in the New Startup category for the Canadian Startup Awards. It recognizes groundbreaking startups founded in 2016.
Finalists include Ada and BenchSci, both based in Toronto, as well as Montreal’s Smooch. Below (in alphabetical order) is a look at each company including how they got started, problems their solving and each one’s Big Hairy Audacious Goal (BHAG) for the future.
Ada
Ada’s customer support automation software-as-a-service (SaaS) is being used by companies like Wattpad, Medium and Telus, providing instant answers to questions in chat. The software leverages machine learning to provide around-the-clock responses through websites, apps, and Facebook Messenger.
Here, Ada CEO Mike Murchison (cofounder and former CEO of social search company Volley) discusses how Ada got started, how it grew and what’s next:
TV: What was the inspiration behind your startup?
MM: In building Volley, we learned how difficult it is to continue to provide high-quality customer support when your company is growing quickly. After struggling to make Volley a daily-use case, we decided to explore opportunities in B2B software for support teams.
To test our hypothesis, David [Hariri] and I became part of the support teams of companies like 500px, Soylent and Kik, processing more than 40,000 tickets between the two of us a month. It was through this very manual effort that we began to build software that enabled us to be more productive support agents.
We soon learned that we could create more value by automating conversations with users before they send an email. Ada was thus born: a SaaS product that empowers support teams to automate answers to users in chat.
What problem are you trying to solve?
30 per cent or more of a customer support agent’s day is spent answering repetitive questions. Ada empowers support teams to focus on higher value customer inquiries.
What is your BHAG for the future?
Our goal is to empower any company to provide an effortless customer support experience at scale.
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BenchSci
BenchSci is “on a mission to help the scientific community achieve biomedical discoveries faster,” says CEO and cofounder Liran Belenzon. He says more than a billion research hours are wasted each year due to the misuse of biological compounds. (You don’t have to be a scientist to know that sounds bad).
“The overwhelming number of commercially available compounds (over 4 million) combined with the poor quality of many of them, has created a challenge that is crippling the pace of drug discovery,” Belenzon said in an email interview.
That’s why BenchSci developed a unique machine learning technology that reads scientific papers, similar to how human research scientists would, to pull out crucial data about the proper usage of compounds.
“With BenchSci, scientists can find compounds that have been proven to work by the scientific community across different research fields,” Belenzon said.
The idea got started after Dr. Thomas Leung, was doing his PhD at the University of Toronto and found, during his research, that many of his experiments failed because of the poor quality of biological compounds. He had to spend hours every week reviewing the literature in order to find compounds that have been proven to work by other scientists, Belenzon says. It was out of frustrated by this process, that he decided to build a machine-learning platform that will help him and the scientific community.
Belenzon offered more insight on the company’s journey since then.
TV: Describe what your company does.
LB: BenchSci was founded last year and is a machine-learning startup that decodes biomedical papers and extracts crucial usage data about biological compounds. With BenchSci, scientists can plan more successful experiments, which leads to a faster drug development process.
What was the inspiration behind your startup?
As a team of PhD scientists who conducted thousands of experiments, we experienced the challenged of finding biological compounds for our experiments. Roughly 50 per cent of new experiments fail because of the misuse of biological compounds. With machine learning technology becoming commercially available and the ongoing movement to open access to scientific papers, we knew this was the right time to solve this problem.
What problem are you trying to solve?
Due to the overwhelming number of commercially available biological compounds … and the poor quality of many of them, scientific papers have become the only reliable source scientists turn to. Unfortunately, current search engines were not designed to find this information in papers.
This challenge forces research scientists to spend four to seven days on average manually searching through the literature to find the specific papers they need. This challenge causes a waste of over one billion research hours a year and is a significant contributor to the reproducibility problem in science.
How is that going?
It is going great! We have partnered with over 100 vendors of biological compounds. In this partnership they provided us with proprietary data that allowed us to decode 4 million scientific papers. In addition, our beta version is being used by 10 universities across North America. We have also generated interest from pharmaceutical and biotechnology industries in our platform.
Who was your first investor?
Our first investor was a family friend that saw how important of a problem we are trying to solve. He wrote the first $25,000 check, which gave us the momentum to close a $300,000 pre-seed round.
What money have you raised since then?
We raised an additional $1.4 million from leading VCs, both in Canada and the US.
What is your biggest success to date?
In addition to being adopted by scientists, our biggest success is our machine learning technology. We built software that can identify the usage of compounds with 90-per-cent accuracy. This is even more impressive because an average PhD scientist has an accuracy of only 66 per cent.
What is your BHAG for the future?
Our goal is to make experiments more successful. We refuse to accept a situation where 50 per cent of new experiments fail because of the products scientists use. Our mission is to make sure that scientists who are fighting to cure life-threatening diseases, have the right tools in their hands.
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Smooch
When was the last time you called a company’s customers service like with a question? Why bother when you can send a message on your phone or computer?
Smooch is one of those companies that helps make that online conversation easier. It’s a platform-as-as-service (PaaS) that helps businesses and software makers work with multi-channel messaging. It started as a project inside of Radialpoint Inc. and was purchased by founders and spun out to become Smooch.
Cofounder and CEO Hamnett Hill gives us some more background on how Smooch got to be so sweet:
TV: Why are you called Smooch?
HH: B2C communication has always been, cold, impersonal and unfriendly. Messaging (and we) make it possible for businesses to create warm, human, personal interactions with their customers, like the kind embrace of a friend, or a Smooch.
What was the inspiration behind your startup?
Most interaction with businesses, particularly phone and email, suck. The rise of messaging (as the primary way consumers communicate) provides the potential to humanize our interactions with the companies we interact with, and make them awesome. Smooch is dedicated to making that happen.
What problem are you trying to solve?
While messaging is the dominant way consumers communicate with each other, businesses are struggling/just starting to use this new medium to interact with their customers. Smooch removes the barriers that get in the way of B2C messaging and makes it easy to create and operationalize spectacular customer experiences across all of the places consumers want to message and communicate.
How is that going?
While messaging as a space is nascent, there are thousands of businesses from start-ups to large enterprise that have started building messaging applications, bots, and experiences and who are leveraging this new communication medium to create great consumer experiences and business value. Already, we have well over 25,000 developers on our platform and manage millions of conversations for thousands of businesses every month.
Who was your first investor?
Our first investors were our founding team, but first external investors were iNovia, Real Ventures, and TA Associates (a previous investor in Radialpoint).
What money have you raised since then?
We announced our $10-million seed round in July/August of 2016.
What is your biggest success to date?
Our biggest successes are the thousands of businesses we are helping to create millions of amazing customer conversations over messaging every month.
What is your BHAG for the future?
Powering billions of awesome conversational experiences every day.
Choose Your Favourite
Which of these deserving young companies deserve to win in the Technology Innovation category? Make sure you vote for your favourites before February 19 at midnight to have your say in which startups should win in their respective categories.
The winners will be announced at a live gala on March 2nd at Steamwhistle Brewery in Toronto.
A Closer Look at the Canadian Startup Awards’ Technology Innovation Finalists
