Yes. The system prompt can include rules like 'B2B SaaS goes to alex@, e-commerce to mara@' and link the appropriate intake URL. The chatbot can also encode budget thresholds, for example routing inquiries under a minimum to a self-service audit form and inquiries above to a partner intake. Updates to routing logic happen in the prompt, not in code, so the firm can iterate as the team and book of business shift. Hand-off is to your existing form, so the bot never holds prospect data in any Sleek-hosted system.

Hand-off is via form or link, so any CRM with a hosted form is supported. The bot does not write directly to the CRM; it routes the prospect to a hosted intake form, which then writes to the CRM with the right pipeline, source, and stage. This separation keeps the data architecture clean and avoids a Sleek-hosted middleware that legal would need to evaluate. For higher-touch hand-offs, the JS API can fire a webhook to your CRM with the conversation transcript when the bot detects a qualified-buyer signal.

Only what is already on your site. Internal-only fields stay invisible, and the system prompt can also instruct the bot to refuse pricing questions and route them to a discovery call. Most marketing services firms keep retainer ranges off the public site for negotiation reasons, and the chatbot respects that exactly because it draws only from published content. If you have a public range, the bot can quote it; if you do not, the bot routes to a fit call rather than guessing.

SleekAI is a paid plugin per site. Many marketing services firms install it for clients on retainer; talk to us about an All Access Pass arrangement that covers multiple client sites under a single account. The widget is brandable per install with colors, logo, avatar, and tone, so a client's chatbot reads as part of the client's brand rather than carrying firm or Sleek branding. This is a common pattern with agency-led implementations.

Yes. SleekAI follows the language of the page and visitor input, and integrates with WPML and Polylang. A firm with English and Spanish service pages can run a single chatbot that replies in either language, drawing context from the matching language's content. Tone can also be language-specific, for example more formal in German B2B contexts and warmer in Latin American Spanish. Vertical-specific terminology gets the same treatment per language.

On your WordPress install. You control retention and exports, and you can pipe interesting conversations to a partner-only Slack channel via webhook so the team sees real-time inbound. For firms with strict client-confidentiality commitments, the fact that conversations never touch a third-party SaaS is often the deciding factor over hosted alternatives. Logs include model name, token usage, and the page URL for attribution to specific campaign pages or referral sources.

It can summarize what a prospect asked about and email it to the appropriate partner, which gives the partner a head start on the proposal. It will not generate full scopes of work autonomously, because pricing and scope decisions belong with the partner, not the chatbot. The bot's job is to capture the brief and route it to the right human, fast. Many firms use the conversation transcript as the first-draft input to the actual SOW, drafted by the partner.

Case studies that have not been published can be referenced as 'a Series B fintech client' or similar abstractions in the chatbot's context, the same way they would appear in a sales deck under NDA. The bot will not invent client names or details, and the system prompt can explicitly forbid disclosure of unpublished engagements. This matches how marketing services sales conversations already handle NDA-bound work, and it keeps the chatbot aligned with the firm's actual disclosure posture.