Finds across every source
registries, requirements, documents and correspondence in one query.
Platform · Data & knowledge Anti-chaos built in
Registries, requirements, documents and correspondence in one connected system. RAG answers in plain language; anti-chaos catches duplicates before they are saved.
Registries, requirements, documents and threads stop being four different truths about the same thing.
One query walks every registry, every document and every thread. What comes back is not ten search results but one reconciled record, with the sources it was assembled from.
registries, requirements, documents and correspondence in one query.
into a golden record with source priority.
similarity, contradictions and anomalies, while the record is still being typed.
who changed what, and a rollback in one click.
Direct message
Platform AI gives you RAG over everything the company runs on: projects, tasks, requirements, requests, documents, correspondence. Through MCP you find what you need in one plain-language query, and before a new entity is written the anti-chaos module checks by itself whether it duplicates or contradicts what is already known. Everything you add makes the knowledge base richer, not noisier.
Registries, tasks, requirements and documents sit in one structure. One query instead of ten APIs — within your role’s permissions.
Before saving, the module looks for anything similar, scores it and offers a merge. You do not create duplicates or contradictions.
A disputed record or a proposed merge lands in the manager’s queue — where the rest of the changes are reviewed, not in someone’s chat.
One registry per entity, rules that hold everywhere, every version on record — and the disputed ones brought to you instead of settled behind your back.
No shadow spreadsheets and no parallel lists in email. The directory, the requirements and the documents live in a shared structure with roles and permissions, and the team argues about one and the same picture.
Required fields, ranges, regular expressions, formulas and dependencies are defined once in the metadata and apply identically in forms, on import, inside processes and over the API.
Every change is recorded: who, when, what was edited and which source the data came from. Comparing versions and rolling back take one click, and the audit trail is preserved.
Anti-chaos does not decide on its own. Near-identical records and contradictions arrive in one queue with a diff, and you accept, reject or send them back with a comment.



Build registries by hand or from a text prompt, a file, even a photo of a diagram. Group them into sections, set attribute types and links between registries. The structure is versioned: adding, renaming and deleting fields keeps a history, without losing data.
Conditional requirements, regular expressions, ranges, formulas, uniqueness checks and logical dependencies are defined once in the metadata of a dataset — and applied in every form, on import, inside processes and over the API. Golden records merge scattered facts about one object with source priority.
Search and the RAG assistant find objects by data, by metadata and by links between registries, in plain language. Before saving, anti-chaos compares the new record with the existing ones: it proposes a merge, highlights contradictions and flags anomalies.
Count what you stop spending
Hunting for a decision through email, private spreadsheets and half a dozen copies of the same directory that have drifted apart costs hours every week and breeds mistakes. One registry with RAG answers the question in a single query — and because the agent works through pre-built, tested blocks instead of generating structure from scratch, it needs roughly ten times fewer tokens to do it.
Uses
Customer stories
A specific scenario, a measurable metric before and after. A specific person who uses this every day.
1 registry
instead of 14 sourceswith duplicates
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Every manager used to “fix” their own spreadsheet, and one invoice got assembled three times over. Now the platform highlights the duplicate before it is saved.
Counterparty master data · B2B holding
Sales, finance and legal each kept their own list of the same companies. Nobody trusted anyone else’s, so every invoice was assembled from scratch — and the same company existed three times with three different tax IDs.
CRM, the ERP directory, two shared spreadsheets and the mail archive — into one registry, without asking anyone to retype anything.
Tax ID format, uniqueness, required legal address. Defined once — and applied in the form, on import and over the API alike.
Similar records are matched by content and structure; the pairs go to the data owner with a similarity score instead of being merged silently.
Sources are ranked: the tax ID comes from ERP, the address from CRM, the contact from correspondence. Every field keeps the source it came from.
Every manager used to “fix” their own spreadsheet, and one invoice got assembled three times over. Now the platform highlights the duplicate before it is saved.
30 seconds
instead of 30 minutesto find the decision
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I ask what we decided on similar incidents and get a ready summary with links. Not from scratch — straight from the decision that was already taken.
Support knowledge · SaaS B2B
Every recurring incident was solved again from zero: the previous decision existed, but it lived in a thread, a ticket comment or somebody’s head. The engineer on shift had no way to find it.
Tickets, requirements, regulations and correspondence went into one system with the links between them intact.
The question is asked in plain language — no field names, no filters, no query syntax to learn.
Every summary comes back with the records it was assembled from, so the engineer can check rather than trust.
Through MCP an AI agent asks the same question and gets the same answer, within its role’s permissions.
I ask what we decided on similar incidents and get a ready summary with links. Not from scratch — straight from the decision that was already taken.
1 day
instead of 2 weeksto launch a registry
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Legal sent over a spreadsheet template — an hour later the registry had its checks, its roles and a link to counterparties. We stopped filing IT tickets for new directories.
Master data · Manufacturing company
Any new directory meant a ticket, a queue and a release. Legal had a spreadsheet ready, but turning it into a working registry with checks and roles took two weeks of somebody else’s time.
The assistant read the file and drafted the registry: fields, types and the links to counterparties.
Required fields, ranges and dependencies were set in the metadata by the person who owns the data, not by a developer.
Who fills it in, who approves, what happens on each status — described once and enforced everywhere.
Renaming and removing fields keeps a history and a comparison, so the registry can change without a migration.
Legal sent over a spreadsheet template — an hour later the registry had its checks, its roles and a link to counterparties. We stopped filing IT tickets for new directories.