What scaling teams get wrong about automation.
How we built the core models that structure thousands of SaaS signals every month.
Product updates buried in changelogs nobody reads. Pricing changes that appear without announcement. Feature launches scattered across press releases, blog posts, Twitter threads, and LinkedIn updates. Integrations mentioned in support docs but missing from marketing pages.
How the models work
We built a pipeline that ingests raw information and organizes it into categories your team actually cares about:
What changed — new features, removed features, pricing shifts
Who it affects — which user types, company sizes, industries
Why it matters — competitive implications, market trends, timing
The models learn from thousands of signals each month, getting better at separating noise from the stuff worth knowing.
What's next
We're working on faster processing, broader source coverage, and better confidence scoring—so you know not just what changed, but how certain we are about it.
More updates soon.
— The Wayan Insight Engineering Team
