Evan Smith is the CEO and Co-founder of Altana AI. He holds a Bachelor’s Degree in Economics from Yale University. Before Altana AI, Evan led enterprise solution and strategic partnership at Panjiva, a trades data science company.
Before Panjiva, Evan co-managed a private equity partnership and the family office sponsor and served as the CEO of IMDU Technologies, a wholly-owned portfolio company providing textile supply chain automation software.
Listen to the full discussion here:
- Listen on Stitcher
Connect with the Guest:
Evan Smith: LinkedIn
Some of the highlights from the podcast:
- Acquiring and selling Panjiva and founding Altana AI
- Taking advantage of the big market opportunities
- Piloting projects on the supply chain insurance side
- Enabling Globalization 2.0 – challenges and opportunities
- How Altana AIis protecting their system from data breach- data privacy, security, and intellectual property protection
- What Altana AI is looking for in terms of talent
- What machine learning means to Altana AI
- [00:58] How did you get to Altana? And why startup?
- [06:18] Is the company coming up with a function to make life more luxurious and better or is the company trying to solve a big challenge in the world?
- [08:12] How do you think that mentality changes when they have this tool of knowledge on their hand?
- [08:36] We’re working with some of the biggest multinationals in the world- Fortune 100, Fortune 500. And what we’re doing is we’re connecting their vendor master data and their building materials into this global map.
- [12:06] When your client is implementing your system, how long does the onboarding take? How long does it take for them to start using the product? And how long does it take for them to really start reading the data and start implementing it?
- [13:41] What about billion-dollar companies focusing on working only on excels with the data points that are not targeted and not segregated the way they want? How do they implement your product?
- [16:01] You are under a very big market, how do a $50 million company kind of answer this big market opportunity?
- [18:09] The next step would be offering those same enterprises a risk transfer insurance solution. We’re partnering up with a couple of the big insurance participants to pilot that.
- [18:17] What is Globalization 2.0?
- [23:17] As the survival pressure gets bigger and bigger, humans will get over their gibberish and organize themselves at scale. And I just believe that our generation is going to be the one that has to deal with earth-scale challenges.
- [24:24] Once the pandemic ends, where do you see yourself? Do you think that the demand on the company will remain the same or are there certain changes to be done? Is it a pandemic thing or do you think that’s actually a new norm and new standard for supply chain?
- [25:26] What I like about what we’re doing is that it is not kind of narrowed to any one problem. So we’re relevant to logistics, to sustainability, to security-relevant, and pretty soon to financial services.
- [26:15] How are you trying to fight data breaches and getting targeted given that you as a company have a lot of data connection points?
- [30:57] What kind of carbon footprints are you using? I’m assuming you’ll need a lot of data centers and you go and outsource or even create your own data centers, do you think about sustainability?
- [32:59] How do you respond to questions regarding carbon footprint? And have you actually seen procurement coming to you with those questions?
- [34:22] What skills are you looking for in terms of the right candidate for your company?
- [35:22] What’s important to us is people who have global experience and are kind of culturally oriented toward high empathy, curiosity, and translation, because we’re building a global business and we’re working to solve some very complicated problems with a bunch of diverse stakeholders.
- [36:17] What would you wish you knew when you started Altana AI? Would you have done something differently if you knew before what you know now?
- [38:28] How is your data going to be beneficial to somebody who is not using it correctly? Is it still going to be beneficial? Are you going to be responsible? Do you have a customer success person within your team who is constantly looking at it? How do you make sure that your customers are being benefited?
- [39:13] What we’re not doing is building a data science consultancy. What we are doing is serving our early adopter customers with white-glove treatment and making sure they get value.
- [40:07] What machine learning means to us is being able to pick up patterns from the data that become reflected in a model that then make predictions or inferences in the presence of new data.