The bottleneck
The information is there, just scattered. The CRM knows who the client is, the ERP holds the invoices, planning knows what's running, and the technical sheets live somewhere in a folder structure. For one simple answer you click between five tools, or you ask whoever happens to know. Dashboards and reports only half solve it: you only find what someone decided in advance to show. The question you have today is exactly the one that isn't there.
How AI solves it
- Ask in plain language: "Which projects are overdue?", "What's our average response time?", "Show me last week's open invoices for client Y." You get the answer right away, without building a report or running an export.
- One chat across all your systems, including a 360° view: the same assistant knows your CRM, ERP, planning, files and technical sheets. Ask "show me everything from client X over the past three months" and it brings together emails, calls, quotes, invoices, tickets and notes in one timeline. A lighter way to get a 360° view than a fixed CRM dashboard, because it picks up exactly the question you have today. The integration layer beneath that 360° view is built in Connect systems and channels.
- Answers with the source attached: the assistant doesn't make things up. It first retrieves the relevant info from your own sources and only then answers, with a reference so you can check it.
- Role-based access: you decide who sees what. Sales gets pricing and history, a technician gets job sheets and docs, nobody sees what isn't meant for them.
It doesn't just answer, it also nudges
The same assistant can also reach out to you or your team. For example: "client X has emailed three times without an answer, take a look", "there are four open quotes above the threshold, follow up?", or "client Y's contract expires in six weeks, schedule a call". It combines what it finds in your systems with the rhythms you've agreed on, and prompts the right person at the right time. How to set that follow-up rhythm in detail is covered in Automate tasks and planning.
RAG: the answer comes from your data, not from thin air
Under the hood this runs on RAG (retrieval-augmented generation). Instead of letting a language model guess, the assistant first retrieves the most relevant passages from your own sources, through a vector store that searches by meaning, and only then forms its answer based on exactly those passages. That's precisely why you don't get invented answers: the model works with your current facts and can point to the source. When your info changes, you simply add the source, no retraining the model. We wrote a broader piece on it: the future of business tools, with AI on your own data.
Systems involved
- A vector store with your own documents, sheets and data
- Connections to your CRM, ERP, planning and files
- A language model that answers from your sources (RAG)
- Role-based access, so everyone only sees what they're allowed to
- EU hosting with zero retention for your business data
What it delivers
- Answers without dashboards, reports or exports
- No more clicking between five tools for one question
- Knowledge that no longer sits locked in one person's head
- Reliable answers, with the source to verify them
- Your data stays inside Europe and isn't kept to train models
Related services
- Platform: brings all your sources together and carries the assistant.
- AI: the models that understand your questions and answer from your data.
Related terms
- RAG: lets the assistant answer from your own facts instead of guessing.
- Vector store: where your documents and data are searchable.
- Embeddings: the meaning vectors that make searching by content possible.
- EU hosting and zero retention: why your business data stays in Europe and isn't kept.
