Scientific foundation
A peer-reviewed framework built with researchers at Michigan, MIT, UC Berkeley, BCG, Xerox PARC, and UC Irvine — and protected by four issued US patents.
Why Generative AI isn't enough
Predicts the next likely token from training data
Generic knowledge, not current context
Single perspective, no structured disagreement
No provenance, no reasoning chain, no uncertainty
Ideas and options are not curated
Orchestrates human and AI reasoning to surface shared intelligence
Private data, your people's knowledge, your context
Cognitive diversity preserved, not averaged away
Every insight traces to specific reasons and contributors
Ideas are reviewed and prioritized for a specific decision
How GCI works
Click each stage. Hover over technical terms for plain-English translations.
The scaling problem
Traditional collaboration complexity grows as n(n−1)/2 — every person must talk to every other person. At 7 people that is already 21 lines of communication. CrowdSmart routes interaction through structured peer review and bridge formation, so complexity grows roughly with n · log₂(n) instead of n². Drag the slider.
TRADITIONAL COLLABORATION
CROWDSMART
Traditional meetings require every pair to communicate — that is the complete graph, n(n−1)/2. CrowdSmart does not ask every participant to review every proposition. Intelligent sampling routes a diverse subset to each reviewer, and clusters are bridged rather than fully connected. The interaction budget therefore grows closer to n · log₂(n) — at 7 people, about 12 routed interactions instead of 21 pairwise lines. The visualization draws the sampled within-cluster edges and the bridges between clusters; the number shown is the formula, not a hand-waved count.
Scientific and strategic advisors
Research, strategy, enterprise, and defense leaders aligned with CrowdSmart's Generative Collective Intelligence vision.
Publications & commentary
Start free, or read the paper first.