GLIV.AI is the autonomous operations platform we built and run for one of our own companies. It drafts the content in the founders' own voice, watches every number, remembers every customer from first hello to graduate, and does the overnight busywork, so two people can spend their hours on the work that matters. Nothing goes out, and no money moves, without a person saying yes.
One of our own companies is a small education business: two founders, several web properties, about 7,000 students and subscribers, and something to publish nearly every day. Running it by hand means being in a dozen places at once, email lists, five payment systems, social groups, search rankings, a calendar full of classes, and a steady stream of new people who each need a warm welcome. Done by hand it eats the whole week and still leaks, and someone always slips through a crack.
GLIV.AI is our answer to that, and it is the clearest proof we can offer that this work is real. It is a single place that watches all of it and does the repetitive parts on its own overnight. We built it exactly the way we build for clients: one automation at a time, each one proven before the next, with a person kept on every decision that matters.
A few of the screens the platform runs. Real people are kept private, so any names or numbers shown in a demo are made up; the software is exactly what we use.
All hand-built: the architecture, the data design, the integrations, the automation fleet, the testing, and the security model.
Code, route, and subscriber counts are from the live system. Availability, latency, and traffic figures on the live app are representative sample data.
Every request hits the same Cloudflare Worker and is sorted into one of three lanes before anything else runs. State lives in Workers KV. Compute is stateless and global.
The landing page, login, opt-in, hosted images, and static assets. Served above the gate.
Where the machine writers push their results: new-student flags, the morning brief, task logs, analytics. Write-only, above the gate.
Every private dashboard read sits below a single 'if not authed' line. That one line provably gates all of it.
Why an edge Worker. No origin to keep alive, no cold starts, global by default, and a security model where one line gates every private read. The whole control plane is one deployable artifact shipped with a single command.
The data spine. Workers KV is fast and global, with a well-known trap: it is eventually consistent, with no atomic read-modify-write. Rather than fight it, the schema is shaped so concurrent writers never collide and reads never fan out. Every engagement event is its own key, so a burst of events never overwrites itself, and each person's summary rides in the key's metadata, so browsing 7,000 people is one paginated list, not thousands of lookups.
A one-operator business cannot babysit its automation, so the platform is built to catch its own regressions.
An endpoint asserts the critical invariants with no side effects, the posting guard holds, categorization is stable, seeding is correct. It returns a pass or a failure, and a nightly agent raises any failure into one attention queue.
Every substantial change runs a rubric self-check, then an independent reviewer against the same rubric: security, correctness, honest interface, house style. Both must clear 95 with zero violations. This page was built under that gate.
Four irreversible classes always wait for a person: move money, publish, message a real person, change a standing rule. The machine prepares; the human commits.
Designed, engineered, and operated by Christopher Grant: the architecture, the control plane, the agent fleet, and the programs it runs. The same building blocks behind every service we offer, proven on our own business first.
Start with a free 20-minute call. We will walk you through the running platform and talk through what a scoped version would look like for your operation.