About DojoStack
Built by operators, for operators.
DojoStack builds the intelligence layer commercial real estate teams have been assembling by hand: property data, assumptions, analysis, and reporting in one auditable operating view.
15+
Years Combined CRE Experience
3
Markets Covered
100%
Transparent & Auditable
24/7
AI-Powered Intelligence
Our Story
From operators who got tired of spreadsheet chaos.
DojoStack was born from years of watching skilled real estate teams lose time to fragmented data and manual workflows. We set out to build the digital infrastructure that lets professionals focus on strategy — not data wrangling.
Replace legacy systems with transparent, verifiable intelligence.
How we build
Power should feel calm.
Our product handles dense commercial real estate work, so the interface has to stay clear, structured, and trustworthy.
01
Domain depth
We build from real CRE workflows.
The product is shaped around rent rolls, tenant exposure, property assumptions, portfolio reporting, and the actual operating rhythm of investment and asset management teams.
02
Controlled automation
AI should make judgment sharper, not hidden.
Every automated workflow must keep assumptions visible, make changes understandable, and leave the user in control of the decision.
03
Product craft
Power should feel calm.
Commercial real estate teams need dense, reliable tools that make repeated work faster without burying the user under noise.
Founders
Domain experience and product execution in the same room.
Martin Cheng
Co-Founder
9+ years of M&A and investment experience. Previously investment manager at Link REIT across China, HKSAR, Singapore, and Australia, and a valuation expert (tech / RE focus) at PwC.
Eins Chu
Co-Founder
6+ years building data-intensive software for Hong Kong's major financial institutions. Previously engineered analytics platforms and enterprise applications for Hang Seng Bank and the Hong Kong Monetary Authority.
LinkedInSee DojoStack on real CRE workflows.
Built for teams that need faster underwriting, cleaner reporting, and confidence in the assumptions behind the numbers.
Contact Us