Field notes from the front line of enterprise AI.
What we learn from the ground — across construction sites, factory floors, labs and hospital wards. Plus engineering perspective from the team building Bizquick.
Why AI-first ERPs will outpace legacy systems by 2026
Legacy ERPs have plateaued. AI-first platforms collapse the boundary between system-of-record and system-of-decision. Here is what that means for CFOs and COOs.
Read articleRead what the team is publishing.
Why AI-first ERPs will outpace legacy systems by 2026
Legacy ERPs have plateaued. AI-first platforms collapse the boundary between system-of-record and system-of-decision. Here is what that means for CFOs and COOs.
Predicting construction delays before they happen
An AI delay-risk score, computed continuously from schedule, weather, vendor and field signals, helps PMOs catch slippage 14 days earlier on average.
Reducing lab turnaround time with predictive scheduling
How a 600-bed multi-speciality lab cut average TAT by 22% in 90 days using AI-driven instrument scheduling and reagent forecasting.
OEE is back: what AI changed about it
OEE has been a North Star metric for decades. AI quality vision and predictive maintenance finally make double-digit OEE gains routine.
ABDM and the rise of consented health data
ABDM-aligned EHRs unlock a new design space: consent-driven, longitudinal records that follow the patient — not the provider.
Micro-frontends in regulated enterprises
We took a 7-product suite to a unified shell using micro-frontends. Here are the patterns, anti-patterns and platform pieces that mattered.
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