Autonomous optimization
On Full autopilot the engine finds, fixes, deploys and verifies on its own — inside the guardrails you set, with every change reversible.
Your clients connect a site with one DNS record. The engine finds, fixes, deploys and verifies at the edge — and gets them cited by ChatGPT, Claude, Perplexity and Gemini. Your logo, your Stripe, your prices.
The level applies to the whole site and can be changed at any time — even mid-run.
See the three levelsSample data · Northwind Cycles
Six parts of the engine, laid out the way your clients meet them in the panel. The numbers are sample data from a fictional client, Northwind Cycles.
On Full autopilot the engine finds, fixes, deploys and verifies on its own — inside the guardrails you set, with every change reversible.
Tracked prompts in ChatGPT, Claude, Perplexity and Gemini.
Crawler visits and AI referrals, kept separate from the answers.
Approval, kill switch, undeploy and an honest CMS boundary.
A real browser opens the page again, and rolls back if it got worse.
Changes are delivered reversibly in the HTML response, not in the CMS or the source code.
The whole engine, grouped. 328 client-facing capabilities across 23 areas, plus the agency and white-label area that only you see.
Five steps in a fixed order, not decoration — the engine runs the whole loop every day, whether or not anyone opens the panel.
The whole site is re-crawled every day — new pages are picked up without anyone reporting them.
88 automated health checks run per page. Findings are ranked by likely effect, not by age.
The fix is written into the HTML that is served, in front of the site — never inside the client’s CMS.
Title, meta description, H1 and schema deploys are re-opened in a real browser afterwards, and fetched as GPTBot, to confirm the change is really there.
If a page got worse, the change is reverted automatically — and you are told that it happened.
A citation is the client’s own page used as a source. A mention only names them. Sources are the domains the answer was built on. Three measurements from the same tracked answers, kept apart — here side by side over twelve weeks. AI referral visits and crawler fetches are counted separately, under Agent traffic.
How often a tracked answer uses one of the client’s own pages as a source. Sampled prompts on a schedule — not access to anyone’s real conversations.
How often the client is named against other brands in the same answer. Being named is not being cited, and it is not a visit.
How many domains the tracked answers built on over twelve weeks — the client’s own and everyone else’s.
We run ten selected prompts per page on a schedule and read which page gets cited, and in which position. Synthetic method — no access to anyone's real conversations.
Synthetic method — we run selected prompts on a schedule and never read anyone else's conversations.
Answer crawlers and training crawlers are not the same. The log keeps them apart, so you see which fetch can actually become a citation.
New crawlers appear as vendors roll them out. If one is blocked, the panel shows which pages it could not read. Sample data.
A separate signal. We measure where they land and how far in they go. Sample data.
48 signals are read, six changes are chosen, and only what passes verification stays. The rest is rolled back automatically. Sample data.
The engine finds the same improvement whatever you choose. The level only decides what happens to it next: it ships on its own (Full autopilot), it ships only if it is a signal that machines read (Invisible-only), or it waits for someone to approve it (Review everything). Below, one real change follows all three paths.
The engine deploys on its own and checks afterwards that the page actually got better.
Signals only machines read (title, meta, schema) go straight out. Text people see on the page waits for you.
Nothing is deployed until someone on your team has seen the proposal and clicked yes.
Changes are layered onto the HTML response, not written into the client's site. So there is always a way back — whatever level you run on.
One row per URL: whether the AI engines have fetched the page, whether they cite it, and what the engine does with it next. A page that has never been fetched does not exist in the answers — however good the copy is. Sample data.
All setup happens in the panel, once per client: control level, guardrails, work limits and alerts. From there the engine runs on its own — you open the panel because you want to, not because it is waiting for you.
That is the whole connection. No plugin, no code on the pages, no access to the client's server.
You run Preferium AI Edge for your clients under your own brand. Connect your Stripe, build your packages, set your prices — every client payment runs on your Stripe and the margin is yours.
Registration opens to founding partners first. Live plan pricing is on the pricing page.
For established agencies and networks: a branded landing page on your own domain with signup, more clients, more seats, audit-logged and isolated.
Scope and onboarding agreed with you.
An autonomous AI-SEO platform built by Preferium AS that agencies resell under their own brand. It connects to a client site through one DNS record, optimizes the HTML at the edge, and tracks who ChatGPT, Claude, Perplexity and Gemini cite. Your clients see your agency, not Preferium.
That the engine finds, fixes, deploys, verifies and rolls back — on its own, every day, within the guardrails you set. With the switches on, nobody has to open the panel: everything is there when you want to look, and every change can be undone with one click.
That depends on the control level. Full autopilot deploys visible changes too. Invisible-only ships only the signals machines read — title, meta, schema — and holds visible text for review. Review everything waits for approval on every change. You pick the level per client in the panel.
Partner registration is not open yet. Leave your details and we will invite you as we open it — or talk to us about Enterprise.