Buyer's agents lose serious enquiries to bad intake. A buyer lands on the site at 10pm after a frustrating weekend of open houses, fills in a contact form with three vague sentences, and waits two days for a callback that may or may not match what they actually need. By Monday morning, the next buyer's agent has already booked the discovery call. SleekAI catches the visitor at the moment of intent, reads the service tier and fee pages directly, and starts a conversation instead of a queue.

The bot pulls from your published service descriptions, fee structures (flat fee, retainer plus success fee, percentage of purchase price), target neighbourhoods, and any case studies stored as posts or ACF fields. When a visitor asks whether you work in a specific postcode or whether your fee is fixed or contingent, the answer comes from the live page, not from training data. Off-market sourcing, auction representation, and relocation packages get explained accurately, and the buyer learns whether they fit before anyone picks up the phone.

Qualification happens in the same conversation. The bot asks about purchase budget, deposit available, mortgage agreement-in-principle status, timeline to complete, and chain position, captures the answers, and forwards a structured summary with the full transcript to your inbox. The consultation that follows is short and focused, the buyer feels heard, and the close rate on the discovery call rises because you already know whether they are a fit.

Buyer's agents win or lose on the discovery call. The buyer who lands on the site at 10pm on a Sunday has just spent a weekend at unsuccessful viewings, has a list of frustrations, and is open to paying for representation if the fit is right. A static contact form throws away that moment of intent.

The buyer fills in three vague sentences, the form goes to a shared inbox, and by Monday morning a competing agent has already booked the slot because their site captured the visitor mid-thought. SleekAI changes that maths by turning every late-night visit into a structured conversation. The bot reads the live fee page and service tier descriptions, so the buyer learns whether the retainer-plus-success-fee structure fits their budget before anyone picks up the phone.

It asks about AIP status, deposit, chain position, and timeline, and the answers land alongside the transcript in the agent's inbox before breakfast. The agent who calls back at 9am opens with context rather than a generic 'tell me about your search', and the call converts because the buyer already feels heard. For multi-agent firms, multibot scopes by area or by named buyer's agent, so a Wandsworth specialist does not field enquiries about Cotswold relocations and vice versa.

Information-stage browsers get the brochure and a nurture sequence, instruction-ready buyers get the consultation slot, and the agent's time is spent where it converts. Conversation logs stored in WordPress give a true picture of which questions buyers actually ask, which areas come up most often, and where the fee structure causes friction, so the service and the pricing can evolve with real evidence rather than guesswork.