For the next interview in our series speaking to technical leaders from around the world, we’ve welcomed Bryan Ovalle, CEO of Hello Llama AI.
Bryan solidified his love of technology studying at Carnegie Mellon University and has spent his career leading from the frontlines of business for leading companies, combining his passions for tech and business to serve and advance P.I.E. (People, Impact, and Empowerment).
Tell us about the business you represent, what is their vision & goals?
We are Hello Llama AI (Llama) and we have brought real active safety to the light electric vehicle (LEV) and micro-mobility industries. Our proprietary system creates a “safety halo” around riders and vehicles using a suite of sensors and on-the-edge AI software that detects dangers from blind spots, collisions, and hazards, and enforces safety regulations like two riders on one vehicle, helmet-wearing, and sidewalk riding. Think Telsa-like ADAS safety technology, but at a price point that makes sense for these lower-cost vehicles.
Can you share a little bit about yourself and how you got into the field of artificial intelligence?
I grew up very modestly in New Jersey with a hardworking and loving immigrant single mother from Guatemala. She always stressed education and growth to gain the skills required to build a better life and options as she was forced to give up her own educational pursuits as a young child to work on the family farm. I went to Carnegie Mellon University where I received a double major and was surrounded by some of the most brilliant minds I’ve ever had the pleasure of connecting with. It was there that I learned being exposed to new methods, tools, and ways of thinking and problem-solving was game-changing and stoked the early fires of how technology could be utilized to solve even more complex problems and develop dynamic solutions. I began my career in aerospace manufacturing where we were constantly trying to improve physical processes at scale, so the drive to improve and increase efficiency was life. I later left aerospace for consulting and strategy roles which is how I landed in the tech industry, starting with SpaceX. The speed and efficiency of improvement and trials digitally were integral to our success and crystallised my desire to marry the early lessons in manufacturing with my love for technology and solving problems.
What do your day-to-day responsibilities look like at your organization?
As CEO of Hello Llama, a large part of my role is centered around fundraising and connecting with customers, while keeping my finger on the pulse of the industry. The other half of my time I invest in developing people, planning & strategizing as well as staying very tight with our product and engineering folks to integrate learnings from the field and customers.
At Llama, we have a decentralized team across several time zones, so Zoom meetings, phone calls, email, and Slack are a way of life for us. We tie it all together and have built our own culture, even though we are mostly remote.
Can you share some of the proudest achievements you've experienced in your career?
While I’m proud of many achievements, I am most proud of the quiet work, growth, and perseverance that was required to reach those moments. I believe wholeheartedly that the real value is in the journey and the destination is where you can take a breath to acknowledge your efforts before you embark on the next journey. One example of this was when I was a first-time manager in my mid-20s and had to defend a multimillion-dollar commercial negotiation from one of our largest customers.
To Tarantino the story, the end is that we successfully defended the claim, raised and won a counterclaim for millions of dollars, and turned a program that was losing money into a profitable business line; all while maintaining the customer relationship. Instead of millions going out the door, we turned it completely around and brought millions in the door – it doesn’t get much better than that, right? Huge victory, heroes of the day…but that work took 10 months, countless weekends, and an extraordinary amount of growth and skills development to accomplish.
Everything from soft skills like leadership and strategy development to tactical research and modeling was needed to win and demanded a higher bar than I had built to date. I had to evolve, had great people around me, and rose to the occasion. When the experience was done, I was changed for the rest of my career. The blood, sweat, tears, ideas, trust, and time invested paid incredible amounts of dividends and rose my bar forever and allowed me to share those skills with others and for that, I am truly proud.
Which industries and processes do you see as the greatest opportunities for applying artificial intelligence?
I would really love to see AI applied to reskilling labour and developing avenues for workers that are displaced by automation and technological advancements. The ability to map skills, traits, transferrable duties, and other factors of declining industries with growing industries and then develop the paths and solutions to enable those transitions would be an opportunity that not only advances AI, but truly advances people’s lives as well.
What are the most significant changes you expect to see in business due to AI?
The speed of development is continuing to accelerate, and I believe AI will continue to evolve from advanced analytics towards machine learning on large datasets to solve complex problems in novel ways with applied AI. Everything from automation and controls to improving business strategies and market research will be influenced by AI in the coming years. AI has gone from science to engineering and now is being thrust into scale across industries. Buckle in, because it’s going to be an awesome ride!
What is your experience with using AI-backed data analysis or log management tools? What do you think is the benefit of using a log management tool that has machine learning capabilities for an organization?
I do not have direct experience with log management tools; however, I am a strong believer in machine learning (ML) and what it can offer organizations. A log management tool that has ML capabilities would be great for log analysis. Using ML for log categorization and pattern learning would allow you to efficiently find log anomalies and deliver root cause reports, resulting in much faster Mean-Time-To-Resolution.