It started with a gym that never replied after office hours.

Looking for somewhere to train one evening, I sent the same question to a handful of gyms. The replies came back the next day, during working hours — by which point I had already joined somewhere else.

The gym that answered first got a member. The others never knew they had been in a race. That is the whole problem Kai Dojo exists to fix, and it is not a small one: most enquiries arrive precisely when the people who could answer them have gone home.

A business does not lose an enquiry because its answer was wrong. It loses it because the answer arrived on Tuesday.

Kai Dojo is one of the things we build.

Cortex Lab AI helps SMEs and startups stay ahead of the competition — from establishing what AI can realistically do for a business, through to running it inside that business. Kai Dojo is one of several products to come out of that work.

We are based in Singapore and have delivered work across several industries, which is the reason Kai Dojo does not read like a generic chatbot: it was built by people who had already learned how differently a gym, a clinic and a factory talk to the people who contact them.

Education
Healthcare
Fitness & gyms
Manufacturing design

Why projects like this usually fail.

MIT studied more than 300 enterprise AI deployments. The model was almost never the problem. Projects stalled on adoption, on workflows that did not match how the job is actually done, and on nobody agreeing what success looked like before the building started.

MIT Project NANDA, The GenAI Divide: State of AI in Business, 2025.

We start where the work is

We ask the owner what outcome they want and the front desk how the job actually moves, then design against both. A person stays in the loop wherever judgement matters.

We start small

The smallest change that pays for itself, shipped in weeks. The next piece is added only once the last one has held up in real use.

We stay after handover

A named owner on your side, an agreed escalation path, and the baseline figures we recorded before starting. A drop shows up as a number on a report, not as a complaint from a customer.

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