OS iXanagi
OS iXanagi recomposes scattered information — not as mere data, but as concepts, relationships, and context.
The first step
Putting your business onto the OS iXanagi foundation starts in one of two places, depending on where your business is today. Either way, the AI drafts and you decide.
Put your business into words and translate it onto the OS iXanagi foundation. You never start from a blank page — you correct the AI's draft on the spot.
Your current site's articles, images and URLs are read in as they are. Nothing has to be re-entered. The articles are grouped by topic and become your company's knowledge.
THE PROBLEM
Write this. Summarize that. Translate it. Anyone can do that now. But you still cannot ask it about your own business — because the knowledge, judgment, and customer signals you’ve built up aren’t in a form AI can use. However smart generic AI gets, it knows nothing about your business, so it guesses from scratch, every time.
There is one reason: the AI does not know your company. Explain from zero each time and you get an answer — but then you are the one thinking, not the AI.
What’s missing isn’t a smarter AI.
The knowledge, judgment, and customer understanding your business runs on — its meaning — isn’t in a form your AI, your tools, or your next hire can use. What’s missing is a foundation of meaning. Your part is to look at what it produces and decide: keep it, or not.
Human-in-the-loop
You sit above the AI. The AI runs the work, but you make the calls. The AI is your agent — never your master.
Sending, publishing, money and deletion happen only with your approval, or within a scope, budget and time limit you set when delegating to the AI. Knowledge, too, is adopted by you as a rule. The exceptions are items whose basis is confirmed in the source material, and items you chose to adopt in bulk at import — and in both cases the reason is recorded. Who asked, what ran and who approved it are recorded.
Who runs it
AI can propose endlessly. Without someone to say “that is not how we say it”, only the volume grows.
“I want this.” “That is not right.” It always starts with your words — a document, a conversation, a recording.
Inside: meaning is extracted
It links what it extracted and proposes — “shall we write this?”, “shall we fix that?” — with reasons. This is where the AI’s job ends.
Inside: meaning is linked
Read, decide. What you need is not a team but someone who can say “that is not how we say it”. About one or two hours a week.
Inside: knowledge is structured
After approval, it is not the AI that carries the work out but code with a fixed procedure. What was done is recorded, and becomes material for the next proposal.
Inside: knowledge accumulates
What becomes possible
Not “more convenient”. These were simply not options before.
Your days
Look at it case by case. On every one of these days, your part is to read and decide.
Open the approval inbox. Three are waiting. Read, decide. Six minutes. Writing, researching and coming up with ideas stop being your job.
Screens are drawn for explanation. Details differ from the actual product.
Workflows and automations
At the heart of OS iXanagi are these two. The names sound technical; what they do is familiar.
Think of a recipe. “Chop, fry, taste, serve” — written down, anyone follows the same steps.
In OS iXanagi, work you do the same way every time becomes a workflow, and the AI follows it. At the points where you decide — the “tasting” in the recipe — it always stops and waits.
Visit the supplier page of every listed item
Find sell-outs and price rises, and list them
Decide: pause or keep (it always stops here)
Update the listings as decided
Think of a rice cooker’s timer. Set it at night, and breakfast rice is ready in the morning.
Book a time on the workflow — an automation — — “every morning at 7”, “the 1st of each month” — and it starts even while you sleep or forget. Instead of a time, an event such as “when an order comes in” can start it too. In the morning you find the results, and only what needs your decision.
Say what you want — “check for sell-outs every morning and tell me”. We build the workflow with the AI and hand it to you. No technical skills needed.
Before anything goes to customers, before money moves — put your approval in the places that matter.
When, what, and in which workflow — you can always look back.
From the developer’s notebook
I’ve built OS iXanagi with my own hands. These are the moments when I caught myself thinking, “wait — it can even do this?”
Curious? Ask the AI directly.
Until now: whoever hunted through articles after each product change
Until now: you, checking your phone
Until now: whoever stalled at “what next?”
Until now: whoever wrote the same thing three times
Until now: whoever copied chat into the ledger
Others vs OS iXanagi
The difference is structural, not cosmetic. This is not an AI built to demo well; it is a foundation built to run real operations.
| Others (generic AI, other tools) | OS iXanagi | |
|---|---|---|
| Knowing your business | Guesses from scratch | Runs on your business’s meaning |
| What accumulates | Nothing | Judgment, customers, and results |
| Page content | Pages, but the content is just text | Knowledge connects and compounds |
| Classification | Tags and categories keep piling up | No tags, no categories |
| Connection | More tools, never connected | One foundation under everything |
| Tie to AI | Locked in to one AI vendor | Your asset is meaning, not a model |
| Made for | Powerful but enterprise-heavy | A company of five can run it |
Apps are not installed; they are activated. No setup wizard starts. An angle you could not see becomes visible. That is all.
| Ordinary apps | OS iXanagi apps | |
|---|---|---|
| To adopt one | Install software | Activate what is already there |
| Adding a second | Migration, double entry, integration work | No migration. Nothing is copied |
| Stopping one | Your data is left behind | Deactivate it. The content stays |
| Connecting apps | Integration must be built | Not needed — they look at the same thing |
Each tool works on its own. But “who we are” gets copied once per tool, and copies always drift.
| What happens every day | The real cause | What happens here |
|---|---|---|
| Rewriting the same explanation per channel | The explanation is duplicated | One explanation. Site, articles and replies draw from it |
| The site and the sales pitch disagree | There is no single source | Fix an explanation and the pages that point to it update; briefs and drafts are marked for review |
| AI needs the company explained every time | No picture of the company AI can read | AI reads the company’s map itself |
| It stops when one person leaves | Judgment stays in one head | Exchanges and decisions accumulate |
| Handing work to AI feels risky | You cannot trace who did what | What the AI sends out passes through approval or a delegated scope, and is recorded |
This problem was solved ten years ago — for large enterprises only. What cost so much was not the mechanism but the people needed to build it.
| Enterprise approach | OS iXanagi | |
|---|---|---|
| Purpose | Govern a huge organization | Let a few people do the work of many |
| Who builds the map | A dedicated team of specialists | AI |
| How you start | Requirements first. Months | By letting it read your current site |
| Price | Undisclosed, large contracts | Public pricing (monthly + usage) |
| Decision | A committee | You |
Numbers with an address
Open any dashboard and numbers appear. Seeing them, what do you do tomorrow? Usually nothing — because why the page was made lives in someone’s head.
What the AI can now say“The aim this page carries is not working on the ‘exam anxiety’ side. The ‘study plan’ side of the same aim gets three times the sign-ups.”
Because there is an address, AI can trace a number back to the decision that produced it.
search records loaded in.
hypotheses from the AI, each tied to an existing aim and citing the searches it came from.
A record of CloudEffects running its own nursing information site through it, on a development environment, on August 31, 2026. These are not today’s figures. Put your site on it and the AI takes the same steps, this far.
How growth shows up
An inquiry, a sign-up, an order — whatever you decide counts as an outcome shows on the “Outcomes (30 days)” card as the number that landed. Open it each month and you can see whether it is growing.
Under the count is “Which claim produced them”. Because every number has an address, you can see which aim is producing outcomes and which is not yet.
“Today’s Suggestions” shows your business maturity as a version number: how many of six areas — knowledge, presentation, analytics, strategy, product and customers — have outcomes starting to flow.
“Not measured” is a month before an outcome goal was set. It is shown apart from a month that was measured and landed 0.
Where it is headed
Both sides, turned by the same mechanism.
Usually the tools that raise revenue and the tools that cut cost are separate and know nothing of each other. Here, an answer given to a customer becomes the next article.
How many inquiries, how many requests, how much revenue. What counts as the outcome is yours to define. The AI’s proposals head toward the North Star you set.
A proposal that cannot say which direction it moves your business is not allowed out.
It will not recommend the next stage before the previous one is met. It is not built to push what we want to sell.
Until the link to outcomes is measured, we say “estimated to help (unmeasured)” and never state it as fact. Silence is never allowed to read as “fine”.
FAQ
Traditional SaaS gives you disconnected features connected by APIs. OS iXanagi models your entire business domain as one semantic structure. Every application is an instantiation of the same ontology.
Every operation declares what it does — read, write internally, send outward, publish, move money, delete, issue credentials, decide — and is handled accordingly. Reading and internal writes run with the asker's permissions, and internal edits keep the previous version. Sending, publishing, money and deletion happen only with your approval, or within a scope, budget and time limit you set when delegating to the AI. The AI cannot issue credentials, and decisions are made by people.
Yes. OS iXanagi includes an 8-module migration pipeline: Import, Extraction, Interpretation, Candidates, Mapping, Apply, Audit, and Post-Migration. For WordPress sites, the pipeline handles both content and structure migration. No server changes required.
No. OS iXanagi is model-agnostic – it is an execution platform, not an AI model. It currently connects to Anthropic (Claude) and OpenAI (GPT). The AI sits outside as a replaceable part; swap it and your assets do not move.
Containerized platform with Docker services. Each tenant gets isolated data with shared infrastructure.
Public prices, in USD. OS iXanagi is $299 a month per brand with every App, every Connector except LINE and WhatsApp, and 5,000 AI credits a month — about 1,000 AI chats or 50 articles ($199 for founding customers, fixed for 12 months). LINE, WhatsApp and voice capture are add-ons at $19 a month each. Each additional brand is $149 with 2,500 credits. Credits stop at the included amount unless you choose otherwise. Enterprise starts at $15,000 a year and Dedicated at $2,500 a month, by quote. Prices are provisional while we tune them.
CloudEffects is the company; OS iXanagi is the product we build.
It is pronounced “O-S Izanagi.” The name comes from Izanagi, from Japanese mythology. It is also a play on words: iXanagi reads as “Intelligence X an AGI.” AGI usually stands for Artificial General Intelligence; here we read it as Artificial Governed Intelligence — AI that people govern.
No. We first read it in and turn its content into a map. Whether to rebuild is a separate choice you make later.
General availability is planned for November 2026 or later. Until then we work with customers individually.
To see how your business is actually doing. We connect only with your explicit consent. Analytics and search data are read-only. When you connect an inbox, we ask for permission to send and receive. You can revoke access from your Google account settings.
No. Sending, publishing, money and deletion happen only with your approval, or within a scope, budget and time limit you set when delegating to the AI. Without approval it stops there. Drafts and internal edits are made by the AI, and the previous version is kept.
Yes. What the AI did, and who approved it, stays on record. You can trace it later.
No. Your company’s information stays in your company’s space. Even brands within one company are kept apart.
No. Changes go one at a time, confirmed as they go. Before anything is applied you can see what will change.
The main actions are reading and deciding. But since a person decides what is right, it needs someone who knows the business.
If you do not approve, it stops there. And the reason for the proposal is kept, so you can trace the cause.
With ChatGPT you explain your company every time. OS iXanagi remembers it, and proposes before you ask.
Put your business into words, then translate it onto the OS iXanagi foundation. That step is the strength of this OS. Once it is defined, sign up and move straight on to automation.
