Running a Successful Machine Learning Startup

Today, our guest, Alain Briancon, will talk to us about how to work with Fortune 500 companies and help them get quick value from their data, how to build a roadmap of incremental value during the data collection and analysis process, how they help predict and incentivize customer purchases, and how to dial in on an idea for successful data science software companies.Alain Briancon: Adding one more question to answer is always easy. The difficult part is what question can I remove and still providing insight.Ginette Methot: I'm Ginette Curtis Seare: And I'm Curtis Ginette: And you are listening to Data Crunch Curtis: A podcast about how applied data science, machine learning and artificial intelligence are changing the world. Ginette: If you’re a fortune 1000 company, and your team needs to be trained in Tableau, Statistics, Data Storytelling, or how to solve business problems with data, we’ll fly one of our expert trainers out to your site for a private group training. The most important investment a business can make is in its people, so head over to our site at datacrunchcorp.com and check out our training courses.Today, our guest, Alain Briancon, will talk to us about how to work with Fortune 500 companies and help them get quick value from their data, how to build a roadmap of incremental value during the data collection and analysis process, how they help predict and incentivize customer purchases, and how to dial in on an idea for successful data science software companies.Alain: My name is Alain Briancon. I am currently the VP of data science and chief technology officer for CEREBRI AI. CEREBRI AI is an AI company, as the name could guess. We are located in three cities: Austin, which is the corporate headquarters; Toronto, which is a hotbed of data science in North America; and Washington DC where I work. What CEREBRI AI focuses on is developing a system to help manage above the strategic component as well as the tactical component of customer experience. This is my fifth startup. This is my third startup that involves data science and machine learning. Jean Belanger, who is the CEO of CEREBRI is a friend of mine; now he's my boss. So I'm trying to work through that, and it took him about 19 years to convince me to join a startup, uh, with him. And this was the right opportunity because the kind of problems we are solving are very challenging.It has been a, an absolute blast. Besides working with a great team and building it up. But when I joined we were about 20 people. Now we're about 63 people, about 50 of them on the technical side. Half in data science, half in software. What has been fantastic is applying tricks and insight that I've gained over the years to, uh, help guide the data science side. The other thing also, which is fun, is we have a very pragmatic view of how to approach things and how to approach engagement with customers. Our customers are fortune 500 customers; they are major banks. One of them is a Central Bank. Others are car makers and we're working very hard into the telco business as well. And, uh, when you deal with such companies, first of all, a very interesting sell cycle in which data science and machine learning play a role at the right moment in time.But you have to also be humbled by the fact that you don't start on their side from a clean sheet. And I think that's one of the most interesting component of making things work is bring data science and machine learning insight to companies who cannot afford and we should not afford the, "okay, let's start from scratch. Let's share all of the data in the like," and so vis Jujitsu between the business case that machine learning brings up and the underlying machine learning technology is one of the most fun element of the work.Curtis: That's interesting. Let's, let's dig into that if we can. Can you give me a concrete example in CEREBRI AI how that works and spell out that concept for us?