The market's next wave
starts in online communities.

8-week rolling windows measure signal acceleration across community types. Developer and academic signals are weighted higher — because they predict where the market is going, not where it has been.

Complaint pattern matching runs across developer forums, community platforms, and Q&A sites. Unmet needs surface as problem-density signals — the raw material for startups worth building.

Every qualifying topic gets a nightly AI-generated brief: the core problem, 3–5 specific startup ideas, market risks, and ranked monetization models. Analyst-level output, automated.

Six propagation stages map the precise position of every trend in its lifecycle. Know whether you are looking at a 9-month window or a 6-week closing window before committing to a direction.

Explosion probability combines momentum, growth trajectory, market whitespace, and stage velocity to quantify which trends are about to break out — before search volume confirms it.

Set score thresholds on any topic and receive alerts the moment opportunity or momentum crosses your threshold. The right signal at the right time, not a digest of noise.

Ask pointed questions about any trend directly. The AI has full context: the topic's stage, velocity, opportunity score, and AI brief. Get specific answers, not generic summaries.

Higher-order meta-trends that span individual topics. When multiple clusters are moving in the same direction, the narrative layer surfaces the structural shift — before it has a label.

Search and filter the raw signals behind any trend. Read the actual forum posts, job listings, and research abstracts driving a score — not just the aggregated output.

Named entities — companies, products, people, places — are extracted from every signal and tracked for velocity, source diversity, and cluster spread. See which names are accelerating across the internet before the narrative around them forms.

HDBSCAN noise points that don't yet fit a tracked cluster are re-clustered at lower thresholds, surfacing embryonic signal groups forming in the gaps. These micro-trends appear days or weeks before the main clustering algorithm picks them up.

Groups of named entities that co-occur in signals more often than chance — brand collaborations, product ecosystems, competitive landscapes. Single-entity velocity misses these. Community detection surfaces the convergence days or weeks before it has a name.