Introducing an AI sales assistant takes four steps: pick the one or two repetitive sales tasks that eat the most time; put the CRM data the assistant will work from in order; try it in a pilot with human approval; then measure and expand. The assistant drafts, summarizes and reminds; the quote and every message to the customer are sent by the salesperson. This guide describes the four steps, the CRM data they need and the metrics to track.

What should the AI sales assistant do?

A large share of a salesperson's time is not customer work: searching old emails, copying into the CRM, building a quote from scratch, keeping follow-ups in their head. The assistant takes over these steps.

  • Summarizing and classifying incoming inquiries. It extracts from the email or form what the customer asks for, in what quantity and by when, and records it in the CRM. The salesperson gets a summary instead of a thread.
  • A quote draft from past offers and the price list. Based on similar past offers and the current price list, it assembles the draft with sources: you can see which line came from which past offer. We describe that system on a separate page: AI quote preparation and sales process automation.
  • Follow-up. Based on the status recorded in the CRM, it reminds you and drafts the follow-up email; the salesperson reviews and sends it.
  • Meeting preparation. It collects the customer history, open quotes and past complaints on one page.

What does it need from the CRM?

The assistant works from what is in the CRM and the systems connected to it. Four things are needed:

  • recorded inquiries and their status: if colleagues do not record leads, the assistant has nothing to work from;
  • past quotes in an accessible form (PDF, Excel or in the CRM), so the draft has something to build on;
  • the current price list in one place;
  • permissions: who may see which customer's data.

Where the information lives in email and Excel today, it has to move into the CRM first. That is often the first half of the project, and the assessment shows it in advance.

Where does a human stay in the loop?

The quote and every message to the customer are sent by the salesperson; the assistant proposes a draft, and sending stays with the salesperson. Price and discount are human decisions. Whatever the assistant cannot fill in with confidence, it flags and leaves to the colleague. We define these rules together during implementation, and the system logs what went out and who approved it.

We offer the quote-drafting system as a service; the details are on the service page. AI quote preparation and sales process automation

How does the implementation run?

  • AI opportunity assessment (from HUF 500,000 + VAT). We review the sales process: where inquiries arrive, where past quotes and the price list live, what the CRM records. The output is a written plan with cost and payback estimates.
  • Pilot. With one salesperson or one product group, in 2-3 weeks. Metrics: response time to an inquiry, time to prepare a quote, share of follow-ups made.
  • Implementation. Integration with the CRM over a secure API, without ripping and replacing; training for the team. Most projects reach production in 6-12 weeks. Source code and models remain yours.

What does it cost?

An AI assistant or integration project is usually €15-40K; the entry point is the AI opportunity assessment, from HUF 500,000 + VAT. The AI ROI calculator estimates the payback with your own numbers. The adoption path for SMEs is described on the AI consulting for SMEs page.

When not to build an AI assistant

If the CRM is not alive, meaning colleagues do not record inquiries, the assistant has nothing to work from; fix the recording first. If the task is a single, always identical sequence of steps (for example, an email to the manager about every new lead), a CRM automation is cheaper and easier to maintain. An AI assistant pays off where inquiries vary and answering them means combining several sources.