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AI Trend Hunter analyzes public signal — GitHub, Hacker News, and RSS — groups it into scored trends, and delivers actionable opportunity briefs. Weak signals in, validated product ideas out.
Sorted by opportunity score · illustrative sample, not live data
Signal pulled from the three places ideas show up first
Reading repos, threads, and feeds across a dozen tabs every week isn't research — it's a part-time job that rarely turns into a decision.
The earliest evidence lives in GitHub repos, Hacker News threads, and RSS feeds, months before it shows up in a trend report or newsletter.
For every real shift there are ten hype cycles. Without scoring, it's impossible to tell a lasting opportunity from a noisy weekend.
A single pipeline turns the flood of public developer activity into a short, ranked list of opportunities, each backed by the evidence it came from.
We continuously collect stars, commits, threads, points, and feed entries from GitHub, Hacker News, and RSS.
Signals are clustered into trends and scored for momentum, opportunity, and saturation, so ranking stays objective.
Each standout trend becomes a short SaaS opportunity brief: who, why now, and where the gap is.
An ingestion layer unifies the three places opportunities show up first, so you stop tab-hopping and start comparing apples to apples.
Every trend carries four numbers — trend score, opportunity, saturation, and momentum — so prioritizing is a glance, not a debate.
No black box. Every score links to the exact repos, threads, and feed entries it came from, so you can verify before you bet.
Top trends get written up as short, actionable briefs: the audience, the timing, and the specific gap a product could fill.
Every session opens with the single best opportunity this week, fully briefed — ICP, competition, MVP to build, monetization, risks — plus four ranked shortlists underneath. No table to interpret first.
One best pick, every session
ICP, MVP, and risks included
Ranked opportunities, not raw data
Start from a ranked list of validated gaps instead of a blank page, and save yourself months of manual tracking.
Filter by category and sort by momentum or saturation to see which niches are heating up and which are already crowded, before you commit.
See which primitives builders are actually adopting, by stars, threads, and release cadence — not by gut feel.
Every score links back to the exact repos, threads, and feed entries it came from, so you can check the evidence before betting on an idea.
Illustrative sample cards showing the score, category, source signals, and brief format every trend arrives in. For a real, dated example, see the real example on the pricing page.
Teams want cost control and data residency without rewriting their stack. Tooling is fragmented with no clear default: an obvious wedge for a managed or self-hosted product.
Flaky-test fatigue meets mature agent tooling. Builders are assembling self-healing test suites, but there's no trusted default: strong demand, moderate saturation.
New AI regulation is forcing teams to document model usage. Demand shows up in feeds and threads before products exist: early, low saturation, high intent.
AI Trend Hunter is live — you can start the 7-day trial today. If you'd rather watch first, leave your email and we'll keep you posted.
Thanks — we'll keep you posted. Whenever you're ready, the 7-day trial is one click away on the pricing page.