AI for the Built Environment

Practical AI-assisted tools
for architectural workflows

Jeddah Hospital 2014
Jeddah Hospital 2014
biomimicry - blue dot mercury filter 2017 - award winner
Manufacturing campus entrance - China 2017
LOAD 2018 - 2nd place award winner
Hisnta Power plant 2018 - Award winner
Pure Land Temple - Taiwan 2021
54 Jeff - 2013
70 Henry St - 2012
Jeddah Hospital 2014
Network Tower - 2018
biomimicry - blue dot mercury filter 2017 - award winner
54 Jeff - 2013
Hisnta Power plant 2018 - Award winner
Network Tower - 2018
70 Henry St - 2012
LOAD 2018 - 2nd place award winner
Pure Land Temple - Taiwan 2021
Hisnta Power plant 2018 - Award winner
Manufacturing campus entrance - China 2017

Jeddah Hospital 2014

Jeddah Hospital 2014

biomimicry - blue dot mercury filter 2017 - award winner

Manufacturing campus entrance - China 2017

LOAD 2018 - 2nd place award winner

Hisnta Power plant 2018 - Award winner

Pure Land Temple - Taiwan 2021

54 Jeff - 2013

70 Henry St - 2012

Jeddah Hospital 2014

Network Tower - 2018

biomimicry - blue dot mercury filter 2017 - award winner

54 Jeff - 2013

Hisnta Power plant 2018 - Award winner

Network Tower - 2018

70 Henry St - 2012

LOAD 2018 - 2nd place award winner

Pure Land Temple - Taiwan 2021

Hisnta Power plant 2018 - Award winner

Manufacturing campus entrance - China 2017

pollution-PM2.5
Computational Design
Rules, parameters, constraints, repeatable intent.
Python Scripting
Geometry, drawings, automation, auditability.
AI Assistance
Structure intent, generate/debug code, document systems.

Computational design systems

Parametric models that preserve intent: controllable geometry, readable parameters, and predictable behavior.

  • Constraint-first setup
  • Geometry that stays editable
  • Rationalization + documentation

Automation + AI assist (headed)

AI supports drafting and debugging, but production stays inside Rhino/Revit where you can verify every step.

  • Scripted generators & checkers
  • Versioned assumptions
  • Hand-off ready outputs