Methodology
How the engine works
The trend detection engine runs on a recurring schedule and scans global news, research and industry sources using neural search. Each candidate article is then analyzed by an AI model to produce a structured assessment. Findings are scored and classified across 21 categories before publication.
The three indicators
Disruption score (1-10)
Higher scores indicate stronger evidence of a meaningful shift with near-term impact potential. Lower scores indicate weaker or earlier signals that may still be emerging.
Commercially viable
This flag indicates signs that commercialization could happen soon, such as deployment momentum, partnerships or monetization pathways.
Paradigm shift
This flag marks potential step-change dynamics where a technology, business model or market structure appears to be fundamentally changing.
The five-layer quality gate
1. Novelty and emergence validation
The model must explicitly determine whether a candidate is genuinely emerging. Established markets, minor product refreshes, seasonal sales and clickbait are rejected before publication. This prevents routine noise from entering the trend feed.
2. Minimum score threshold
Findings below the minimum disruption threshold are discarded. The current save threshold is 4, so candidates scoring under 4 are filtered out even if they are novel. This keeps the published set focused on meaningful signal strength.
3. Source quality filtering
Candidate selection prioritizes higher-authority sources, and lower-authority domains face a stricter save bar. In practice, those sources are only accepted if the assessed disruption score is very high. This mechanism reduces promotional or low-trust content without publishing internal source lists.
4. Duplicate detection
Candidate URLs already stored as findings are skipped. This prevents duplicate entries and keeps each item in the feed linked to a distinct source article.
5. Strict scoring rules
Vague, promotional and listicle-style content is penalized, and low-substance articles are capped at a score of 5. Scores of 7 or higher require genuine technological breakthroughs, new market categories, or fundamental shifts backed by concrete evidence. These constraints are designed to keep high scores rare and defensible.
What gets rejected
Most candidate articles do not become published findings. The feed is intentionally curated: items are filtered out when they fail emergence checks, score thresholds, source-quality requirements, or duplicate checks.
Source traceability
Every published finding links directly to its original source URL. This allows readers to verify claims and inspect the underlying material that informed the score.
Limitations and disclaimer
The engine is designed to surface early signals, not certainties. Scores and flags are model-generated assessments based on available content and may be incomplete or wrong. All content is provided for informational purposes only and does not constitute investment advice.