Finn started Tacita after a year of building Tess on his own. Tess is the AI now used by W Advisers, a Sydney boutique law firm, for discovery and document review. It runs on open models on a Mac Studio in Finn's bedroom.

The goal was simple: build the best legal AI in the world, alone, without shortcuts or institutional data, running on consumer hardware. Tess hits highs comparable to Legora, the strongest commercial legal AI to date, without the polish or consistency that comes with four hundred staff and eight hundred million dollars. This experience gave him a working understanding of what current models can and cannot do, where the field is going, and which consensus opinions about it are wrong. Tacita is built on that understanding.

Before Tacita, he was a systems engineer at Raytheon Australia, working on the Australian Defence Air Traffic System, and conducted machine learning research for Rio Tinto, building Bayesian models to optimise sample placement on large-scale geological surveys. His academic research was in autonomous robotics, designing novel computational methods for coordinating micro-drone swarms to replicate bird flocking behaviour and then learning to herd them. He holds a First Class Honours degree in Mechatronic and Space Engineering and a Bachelor of Science in Advanced Physics from the University of Sydney.

Finn sees Tacita as the right vehicle for frontier AI research into the decision-making, knowledge representations, and reasoning patterns of the most effective humans. He believes this work is missing from the current research landscape and only possible through applied engagement, not from a lab.

The rejection letter from his Stanford Aeronautics and Astronautics PhD application is framed on his desk. If a deal falls through, he might frame that too.

Declan came to Tacita after spending the better part of a year building an AI for small Australian property managers, in parallel with his masters. Around the same time, a small hedge fund approached him to build something similar in their domain. He joined Tacita because building the work for either of them alone was a worse use of his time than building it for both.

Before Tacita, he was an electrical engineer at Nanosonics, the ASX-listed medical devices company, where he worked on the development of Coris, the next generation of their core platform. He has also done machine learning research at Nucs AI on tumour segmentation pipelines for prostate cancer diagnostics, biomedical engineering at NSW Health on the medical device fleet of Royal North Shore Hospital, and operations automation for Navbit, a surgical engineering firm.

He holds a Bachelor of Engineering Honours in Biomedical Engineering and a Bachelor of Medical Science from the University of Sydney, and is completing a Master of Quantitative Finance at UTS on a postgraduate scholarship.

Declan treats Tacita as the right place to do the foundational work that any serious AI deployment in a high-stakes domain will eventually need. Medicine is one of the domains he hopes will benefit from that work.