We exist because three things are true simultaneously.
If any one of these were false, Mitori would not need to exist.
Most AI programs fail because they start from assumptions instead of observed work.
Interviews and system logs miss too much of how knowledge work actually happens.
AI deployment needs operational evidence, trust, and rollout discipline to be credible.
Why Mitori
Mitori (見取り) is a concept from traditional Japanese martial arts. It means to read a situation so completely — every movement, every pattern, every underlying structure — that you understand what will happen before it does. Not just observation. Comprehension.
There is a second meaning: mitori geiko (見取り稽古) — the practice of mastering a skill purely by watching. No instructions, no shortcuts. A student watches a master with disciplined attention until the pattern becomes clear. It is one of the most demanding and most respected forms of learning in traditional Japanese arts, because it requires the student to supply their own understanding, not receive it pre-packaged.
We chose this name because both meanings describe exactly what we do. We observe before we conclude. We watch before we recommend. We look at how your organisation actually works — not how it's described, not how it's logged, not how it performs in a workshop — and we watch until the real structure becomes visible. Then we tell you what it means, and we build what comes next.
There is a third meaning we are transparent about: 看取り (also mitori, written differently) is the Japanese word for being present with someone as they die. We are not being morbid. We are being honest. The most useful thing we do is look at the parts of organisations that nobody else has looked at carefully — the work that exists in the gap between job descriptions and reality, the roles that have quietly outgrown their original purpose, the processes that nobody has re-examined because doing so is uncomfortable. We observe those things with care. And then we help teams redesign what comes next.
We called ourselves Mitori because every meaning is true.
AI transformation programs fail at a rate of 95% when it comes to scaling beyond initial pilots. The problem is not the AI. The problem is that organisations don't know what they're actually asking the AI to automate, augment, or redesign.
Consulting firms charge millions to answer this question — using interviews, workshops, and self-reported data. Process mining tools only see what makes it into a system of record, missing 60% or more of actual knowledge work.
Mitori was founded in 2026 on a simple insight: the gap between what people say they do and what they actually do is where AI transformation fails. Nobody had solved this. So we did.
We built a platform that observes organisations at the structural level — the real mechanics of how work happens — and then deploys AI agents trained on that observed reality. Not on job descriptions. Not on interview transcripts. On ground truth.
Our mission
To give every organisation a true, observed understanding of how they work — and the AI agents to transform that understanding into action.
Team
A lean, product-led team focused on usability, trust, and customer satisfaction.
James McCombe
Founder
Leader and founder with a track record of building innovative tech solutions.
Leo Liu
CTO
Technical architect overseeing platform scalability and security.
Jamie Bryant
Marketing Consultant
Strategist driving brand awareness and community engagement.
Ladana Boskett
Marketing Executive
Executing campaigns that connect operators with the tools they need.
Jin Kuk
Engineer
Full-stack developer building robust and responsive user experiences.
Advisor
Senior perspective across regulation, strategy, and enterprise operating environments.
Daniel Trinder
Advisor
Bringing decades of financial regulatory and strategic expertise.