About Ryto
Watching the web change over time
Ryto is a long-polling contextual-intelligence tool. It gives AI agents memory of the live web — not just what a page says, but how it changed to get there.
Most ways of giving an AI agent knowledge of the live web are snapshots: fetch a page, read it, throw it away, fetch it again next time. That's expensive, and it's blind to history — the agent only ever sees what is, never how it got there.
Ryto keeps the time axis. It watches a set of external sources on a respectful cadence and turns every pull into a timestamped point in a series. The current state is always one read away; the trajectory — what changed, when, and by how much — becomes a query, not a rebuild. An agent reasons over a compact timeline of changes instead of re-reading the whole web on every question.
How it watches a site over time
Each source is checked on a schedule. When nothing has changed, Ryto records that cheaply and moves on — a conditional request costs the source almost nothing. When something does change, it captures an immutable snapshot, computes the difference from the last one, and appends a new point to the timeline.
Over days and weeks, that timeline becomes the thing the agent actually reasons about: not a wall of HTML re-read from scratch, but a sequence of "here is what was true, and here is what moved."
What an agent can reason about
Competitor pricing
Snapshot a pricing page twice a day. An agent can answer "their Pro tier dropped 12% three weeks ago" without re-scraping the page itself.
API docs & changelogs
Catch a new endpoint the day it appears, or a deprecation the moment it's announced — and tell an agent exactly which call to migrate.
Policy & terms
Know when a vendor's terms changed, with the before/after, so an agent can flag the one clause that actually moved.
Hiring signals
Watch a careers page over time; a sudden burst of robotics roles is a trend an agent can reason about, not just a list it re-reads.
Status & availability
Track a dependency's status page across weeks to reason about reliability trends — not just the banner showing right now.
Anything that drifts
Docs, rankings, inventory, sentiment — if a page changes slowly and the change is the point, it belongs on a timeline.
Two questions, not one
What is — the current state, always one read away.
What changed — the trajectory over time, queryable as a series.
Conventional fetch-and-read only ever answers the first question. Ryto answers both, efficiently, so an agent spends its reasoning on the change rather than on re-reading everything that didn't.
Ryto is built on RelayPlex, and is the first consumer of its scheduling-and-control primitive — the scheduled, respectful egress that turns "watch the web over time" into a platform feature instead of an external runner you have to babysit.