Natalie Nguyen co-founded Hyper Anna, an AI-meets-fintech software that quickly codes, processes and analyses large amounts of data. Now, they're going global.
Natalie Nguyen makes a great argument for studying coding and other STEM (science, technology, engineering and mathematics) subjects in school. Starting in grade six, Nguyen channelled her enthusiasm for puzzle-solving into pet projects such as programming a better book-borrowing record for her school library in Vietnam.
“Everything used to be recorded manually on paper, so I just approached the principal and asked, ‘Would you be interested in me writing software and the school could try it?’ It was just a fun thing — and a great learning opportunity.”
After coming to Sydney to complete a design computing degree at the University of Sydney, she returned to Vietnam. A little more than a decade later, Nguyen’s passion for coding put her on the frontline of the “big data revolution”, working as an analytical lead at Quantium, a data and technology development company, 50 per cent-owned by Woolworths. Like many analytical roles, the work involved similar routines every day.
“Up to 80 per cent of my work was actually very repetitive and purely technical,” she recalls. “And it didn’t really require higher level skills, like problem-solving or business acumen.”
She’d look into a question from the business, translate that into an SQL (database language) query, analyse the results and then build visual narratives in PowerPoint to explain her findings to her co-workers.
“Most of the questions were quite similar and I really wanted more meaty problems,” she admits. “Because of this frustration, I was passionate to create Hyper Anna — basically to automate a lot of those manual, repetitive tasks.”
Hyper Anna is a data scientist, like Nguyen, who can write her own code to process and analyse huge amounts of data, and can then present the insights in graphs that make sense to other people in the business so they can make decisions. Unlike Nguyen, Hyper Anna is an entirely artificial intelligence
Launched in early 2016, Hyper Anna has grown quickly, thanks to two rounds of funding totalling more than $17m — including enthusiastic support from tech-venture guru Daniel Petre at AirTree Ventures. Equally important, it has lucrative contracts with financial sector heavyweights such as Westpac and IAG.
Freeing up human minds
Nguyen says she’s not interested in AI for the sake of it, although she created Hyper Anna because she felt the technology was mature enough to take on the repetitive tasks consuming most data analysts’ hours, and complete them faster. “I felt everything in AI was aligning at the right time to be useful,” she explains. “Hyper Anna proactively uncovers insights and answers plain English questions about your data in a matter of seconds, to help you make smart and fast high-impact decisions. For business users, Anna allows quick self-serve insight. For analysts, she frees up time spent building dashboards and answering routine questions to allow more time for high-value initiatives.”
Companies that want to innovate should also want to understand their customers’ pain points, she observes, suggesting there’s much to be gained meeting them in a safe and trusted environment to hear unfiltered feedback.
Growing up fast
While proud to be named on Forbes “30 under 30 Asia” list in 2019, Nguyen positively beams when describing her experience at a recent Hyper Anna user meet-up.
“One of the analysts in the room said, ‘With Anna, I can now focus on learning new skills instead of just doing a lot of routine ad hoc questions.’ I felt particularly proud because it shows that I’ve started to solve the problem for people like me.”
Nguyen predicts the next generation of analysts and coders will have more freedom to explore bigger questions because coding language will become more human-like, with a shorter learning curve. She believes the beauty of creating software is not in knowing how to code, but that she can identify a problem — and a reasonable solution that works — in a short amount of time.
“Not having to do mundane tasks, we get to use our time more wisely and apply our experience,” she says.
“In business today, a lot of time is used to transfer knowledge. Now, with technology doing a lot of capturing of the data and analysing it, we can transfer knowledge in a much more autonomous way. That will be very exciting for the future workplace because we can spend more time using our business acumen and moral compass to make better decisions.”
AI myths
- AI isn’t ready yet “I hear a lot that AI is this concept that will happen in the future. Actually, there are a lot of applications using AI tech already. It’s been around for a number of years.”
- AI will replace a lot of jobs “AI is a task replacement, not a job replacement. Just because we’ll replace a lot of the more mundane, ad hoc, repetitive and routine tasks, doesn’t mean we’ll replace the entire job.”
- AI is unbiased “Every single data point created by people has some bias, so we need data scientists working on minimising the bias. The limitations aren’t talked about enough.”
- AI is a silver bullet “AI will supposedly solve every single problem end-to-end, but that’s certainly not the case with the current technology. It’s just another tool, a very powerful tool, but still a tool. You need people to make decisions.”
Advice startups need
- People who teach accountability through action “Accountability between mentors and founders is bi-directional. I had a mentor who took notes on every discussion we had, making a point to ensure I did what I said I was going to.”
- People with experiences in areas founders don’t have “[Board member] Daniel Petre AO GAICD taught me to hire people better than me, especially in parts of the business I’m still learning. As a business owner, you need to be open to constructive criticism so you can deal with hard problems — such as product-market fit — if you want to propel innovation.”
- People who know what customers need “We’re focused on creating painkillers, not vitamins. To be successful, your solution should be a must-have, not a nice-to-have.”
- People who are focused on sustainable growth “A high percentage of tech startups are founded by people with backgrounds in tech, not business. We want our board members to give us practical advice about growing and governing the company sustainably. [Board member] Danny Gilligan reminds me it’s not a sprint, but a marathon. Founders want more advice than you think because we can benefit a lot from our board members’ experience.”
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