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Personalisation: an AI that knows the logged-in customer

When the user logs in, coreAI goes from answering everyone the same way to answering this exact customer. The assistant knows who is asking, fetches from the customer's own orders, cases, and agreements, and tailors answers, recommendations, and actions to the context – within the access the account already has, without you building new access logic in the AI layer.

Personalisation in coreAI means that a logged-in user gets answers that apply to exactly them – not a generic default answer. The moment the customer is logged in, the assistant knows who it is talking to and which data it is allowed to use on behalf of that user. It can then answer "where is my order?" with the customer's actual order, suggest what suits this specific account, and carry out actions that concern the customer's own cases. Logged out, coreAI gives good, general answers from your knowledge base; logged in, it gives personal answers built on the customer's own context.

Comparison of the same question logged out and logged in: logged out gives a general answer without personal data, logged in gives a personal answer based on the customer's own order and within their own permissions
Comparison of the same question logged out and logged in: logged out gives a general answer without personal data, logged in gives a personal answer based on the customer's own order and within their own permissions

#What login unlocks

The difference between an anonymous and a logged-in conversation is access to context. As soon as the user is authenticated, the assistant can connect the question to an identity and to the data that belongs to that identity.

  • Identity-aware answers – "When will my package arrive?" is answered with the customer's own order and tracking status, not with a general explanation of delivery times.
  • Data from the customer's own systems – the assistant fetches from order history, subscriptions, cases, and agreements that belong to the logged-in user.
  • Role-based content – an administrator, an end user, and a partner see answers tailored to what their role actually has access to.
  • Personal recommendations – suggestions build on what the customer has bought, viewed, or asked about before, instead of a generic bestseller list.

#Personalisation isn't just personal – it's access-controlled

Personalisation isn't only about the individual customer. Often the point is that a logged-in user should see content that applies to their role or group – not just their own personal data. Behind login, coreAI therefore fetches from internal, access-controlled knowledge bases that are never visible to anonymous visitors: intranets, HR handbooks, membership terms, supplier agreements, or customer-specific prices.

Two users can ask exactly the same question and get different – but correct – answers, because each request is scoped to the set of sources the user actually has access to. An employee gets answers from internal routines, a supplier from their agreements, a logged-in customer from their own terms. We often recommend several knowledge bases with different access – one public and several behind login for customers, suppliers, and employees. See even better answers behind login for how role-based knowledge bases are set up.

The access is validated against your own login system, not against a user registry in coreAI. If you set a callbackUrl on the assistant, coreAI calls your endpoint with the user's token and only lets through what the user should see – and can lock the conversation to specific data sources per user or organisation. The details are in protect an assistant with your own login.

#From personal answers to personal actions

Personalisation becomes truly powerful when combined with agentic AI. A logged-in customer can not only get answers about their own order – the assistant can change it. Because the identity is known, coreAI can carry out actions that concern this exact customer:

  • move the customer's own delivery to a new date
  • update contact details or address on the account
  • create a case tied to the customer's own history
  • cancel or change a subscription the customer actually owns

The actions always happen on behalf of the logged-in user and never on anyone else's data.

#You keep control of access

Personalisation in coreAI reuses the access control you already have – it introduces no new one. It is your line-of-business system, not the AI layer, that decides what a given logged-in user gets to see and do. A customer reaches their own orders but not anyone else's; a case worker operates within their own department. The same role-based access (RBAC) that governs the rest of your systems also governs what the assistant can fetch and do.

If the user is not logged in, the assistant safely falls back to general answers from your knowledge base. Personal data never appears before the identity is confirmed, and everything runs on your own infrastructure – not in global models. See the knowledge base solution to understand how the content and data fit together.

#How to get started

Connect the login and the systems that hold the customer's data, and coreAI builds the personal layer on top of what you already have. The assistant answers everyone well when logged out, and becomes personal the moment the customer logs in. Get in touch for a walkthrough of what personalisation can offer your logged-in customers specifically.