Use the embedded agent
Nothing else to connect. Log in, start chatting and upload your product files. The agent interviews you and builds the draft inside the platform.
Log in and work with the AI agent embedded inside InoatriX. Give it your specification files, answer its questions and let it configure the product with you. Switch to the no-code studio at any moment—or bring your own AI agent through MCP.
Use the agent already inside the platform or connect your preferred one. Either way, your team can take over visually at any point.
Nothing else to connect. Log in, start chatting and upload your product files. The agent interviews you and builds the draft inside the platform.
Connect any assistant that speaks MCP — the open standard for linking AI to outside tools — and create governed drafts with the AI tooling your team already uses.
How to connectBoth agent paths and the visual studio operate on the same product. Switch tools without exporting files, recreating work or losing context.
The agent does not just ingest a specification. It works with you to make the product complete, then lets you continue in the interface whenever that is faster.
Start a conversation inside InoatriX and upload the documents and spreadsheets you already use to define the product. The agent reads them in the context of the platform's real configuration capabilities.
It identifies gaps and ambiguities, asks focused follow-up questions and confirms the decisions needed for risk objects, coverages, plans, rules, lifecycle and pricing.
The agreed specification is checked before it is written. The agent configures the product in the platform and keeps you informed as the draft takes shape.
Open the same draft in the Product Configurator, inspect or change any setting yourself, and return to the embedded agent whenever you want. Your team remains in control of publishing.
The interesting question about AI configuration is not what it can build. It is what it cannot reach.
Publishing is not something a connected assistant can do — the ability is absent from the connection, not merely discouraged. Going live stays a human decision.
An assistant can tidy up drafts it created and nothing else. A product that is live, or that someone else is working on, is out of its reach entirely.
Every value the agent set is a normal field in the configurator. There is no AI-only state, and no setting your team cannot see, change or override.
If a build step fails, the partial draft is kept and the failure is reported—so you inspect what exists rather than guess what happened.
Each connected assistant gets its own private key, and acts under an identity of its own. Every draft carries the name of whoever created it, so it is always clear which assistant did what.
A configured draft is structurally complete but not pretending to be underwritten. It is a starting point for review—which is exactly what it is presented as.
Any MCP-capable assistant connects — ChatGPT and Claude are simply the two we publish ready-made settings for. It takes about fifteen minutes and no code: a key, an address, and a restart.
Walks through every step in plain language: the key we issue you, pasting the settings, checking the connection worked, and what to do if it does not.
Upload what you know, let the agent ask about what you do not, and open the visual studio whenever direct configuration is the better tool. Every route leads to the same governed draft, and the decision to go live stays with the people accountable for it.