Using AI to Wrangle Massive Amounts of Data – Deckard Technologies Featured in Create Australia

Earlier this month, I was invited by Create (by Engineers Australia) to be part of a video they were producing on AI, with a focus on Australians working in the space. It was fantastic to be included in this piece, as it provided an opportunity to showcase the advanced AI-driven GovTech solutions we're developing at Deckard Technologies.

The piece focused on Deckard Technologies’ use of AI and featured academics and industry experts speaking about the responsible use of AI in the government sector. Here is a link to the article and the full video can be seen here.

As an overview, I was able to talk about Deckard Technologies, one of the top GovTech companies in the US and Australia, and our mission of assisting local governments in navigating the complexities of short-term rentals (STRs) and effects on housing supply. By processing vast datasets through sophisticated GovTech machine learning and statistical modeling, we are able to transform raw data into actionable insights.

For us—at the scale we operate—AI is not just a convenience, it’s a necessity. Once you reach a certain volume of data, human analysis alone simply isn’t fast or scalable enough. AI can process information and make decisions at a speed and level of reproducibility that humans can’t, ensuring accuracy and consistency across massive datasets. But technology alone isn’t enough—we pair these powerful models with human oversight, ensuring they remain resilient, fair, and effective—especially in the context of GovTech software used for modern government operations.

Beyond analytics, we prioritize robust data governance and security. Our clients entrust us with sensitive information, and we uphold strict compliance standards to protect personally identifiable information (PII). While AI enables us to extract meaningful patterns from trillions of data points, we recognize that human expertise is indispensable in monitoring systems, ensuring ethical AI practices, and adapting to evolving challenges.

Participating in this article was an exciting opportunity to discuss the intricate systems we've developed and to highlight the collaborative efforts of our team in delivering reliable, up-to-date insights to our clients.

“To make sure that this process is resilient, we have an immense amount of data monitoring, data pipeline monitoring, making sure that if these data pipelines fail, we’ve got engineers that can go look at them pretty much immediately,”
Deckard Technologies’ Co-Founder and VP of Data Science, Tony Moriarty, told Create.

Tony Moriarty – VP of Data Science, Deckard Technologies