Hey, this is Aaron, thanks for engaging on this. I really think I've got something here and can't wait to get your feedback. I've got traveling to do today and tomorrow morning, so should be available if you want to chat, and will "likely" have a fully self serve version for you to start using tomorrow. Below here the information was generated, at my direction, by a GTM AI Agent process using relayplex as the platform for hosting. Please let me know if I've presented any use case information that inspires some imaginative use cases!
ryto.pro · a RelayPlex testing ground
For Mohammad
Two things you could build on RelayPlex — a go-to-market surface for Cavalla you could ship today, and the AI-agent world Cavalla is heading into.
This whole domain is my personal testing ground for building with RelayPlex — a platform that hands you hosting, durable state, secrets, and auth as a few composable primitives and gets out of the way. New site, live instantly, no DNS or SSL wait. Everything you see under ryto.pro is me pushing on what the platform can carry.
Here's what I think you could build with it — one piece for today, one for where Cavalla is going.
Go-to-market for Cavalla
A warehouse-robotics company's GTM is, underneath, mostly hosting + data + lead capture + secrets. That happens to be the entire RelayPlex primitive set, so the whole surface is a weekend, not a quarter:
- A site at any subdomain, live the moment you create it — marketing pages, a pilot portal, a careers page.
- Published data buckets — specs, integrations, case studies as JSON that both your own pages and other people's AI agents can read. An agent researching warehouse automation can pull Cavalla's feed directly.
- Lead capture that's private by construction — demo requests and design-partner signups land in an append-only, owner-read-only bucket. The form ships a token that can only write, never read back.
- A vault for secrets — CRM, email, enrichment keys used server-side by reference; the secret never leaves the platform or enters a page.
- Gated sessions — put the investor deck or the pilot dashboard behind a login verified at the edge.
Marketing site, an agent-readable product feed, and a design-partner intake — all on one primitive set, all yours.
AI-agent scheduling control for local compute
This is the one that matters for where Cavalla is heading. Today RelayPlex owns state, hosting, and secrets. The leg still in development is scheduled, stateful compute that can reach out and coordinate with compute that isn't ours — specifically, compute sitting on the customer's own node.
Picture deployed robotics. The back office — fleet orchestration, telemetry rollups, the software that actually runs a warehouse — has to live close to the robots, on the customer's hardware, for latency and for control. Standing that back office up is slow today because the software was never built for the way it'll actually be operated: by AI agents.
RelayPlex's roadmap is to make software for AI agents first-class citizens — a scheduling and control primitive that lets an agent dispatch, schedule, and supervise work on a customer's local compute node, deterministically and auditably. The ambition: deploy the back office of a fleet up to 20× faster, because the agent is the operator and the platform gives it a safe, scheduled way to act on local hardware.
Coordinating with local compute under deterministic security is the only way RelayPlex can give enterprise clients paranoid-grade IP protection. The IP stays on the customer's node; the agent reaches it through a governed schedule — never by shipping the data out.
Enterprise robotics buyers will not let their layouts, models, or operational data leave their walls. So the platform can't be "send us your data." It has to be "your compute stays yours; we coordinate it, on a schedule, under rules you can audit." Deterministic security — default-deny allowlists, secrets used by reference, append-only owner-read trails — is what makes that coordination safe enough for the most paranoid buyer in the room.
Why I'm building Ryto on this
Ryto is a long-polling contextual-intelligence tool: it watches external websites change over time and lets AI agents reason about those changes efficiently, instead of re-reading the whole web on every query. To do that, Ryto needs exactly the scheduling-control primitive that's in development — pull from sources on a respectful cadence, turn each pull into a timestamped point, and compute what actually changed.
I'm building it on RelayPlex partly as a forcing function for that primitive, and partly to show the platform can carry a genuinely complex solution — not just a static page. Ryto is the proof that the roadmap above is real work, already underway.