Insights
Ideas behind trusted sports intelligence.
KENNDA publishes clear thinking on the technical and market principles behind athlete evaluation, discoverability, explainability, market context, data quality, and responsible AI.
Evaluation
Why athlete evaluation needs more than performance statistics
Performance matters, but useful athlete evaluation also needs development history, position context, verified measurables, recruiting trajectory, and reliable evidence.
August 20265 min read
Responsible AIIn high-stakes AI, trust has to be a product feature
Explainability, lineage, model versioning, and human oversight are not back-office controls when decisions affect real athletes and institutions.
August 20264 min read
CompanyWhy the long-term moat is the intelligence system—not one model
Durable advantage compounds across athlete identity, proprietary data, domain features, labels, comparables, lineage, and real evaluation workflows.
August 20266 min read