Yes, for standard published programs. Per-seat list price, cohort size caps, and add-ons like extra coaching hours or sponsor consulting live in postmeta. The bot can multiply seat count by tier price for a quick estimate. For multi-year master service agreements or custom-built programs with negotiated pricing, the bot is instructed to capture scope and route to the account team.

Methodology articles, case studies, and white papers can be indexed via OpenAI Files so the bot quotes your actual approach (action learning, peer coaching pods, simulations, business challenges) rather than generic leadership development language. A buyer asking 'do you use action learning' gets a concrete answer with the specific way you apply it, not a textbook definition.

Yes. Enterprise L&D usually has a head of talent, a head of L&D, an executive sponsor, and a procurement contact. The system prompt can guide the bot to capture who is doing the asking and route to the right intake. A head of talent doing initial vendor research needs different content than a procurement officer comparing finalist firms; the bot can branch the conversation accordingly.

Yes. Outcome data from case studies (promotion rates, retention deltas, 360 score changes, sponsor satisfaction) can live in ACF fields or be indexed via OpenAI Files. When a buyer asks 'what kind of results have you seen,' the bot cites real case studies rather than inventing numbers. This is the single most important capability for enterprise L&D evaluation, where unsupported outcome claims sink credibility quickly.

Yes. Regional facilitator availability, language coverage, and delivery hub locations can live in custom fields per region. A buyer asking 'can you deliver in Singapore in Mandarin and English' gets a specific answer based on your real facilitator pool rather than a generic 'yes we deliver globally.' For firms with uneven regional coverage, this honesty preserves credibility better than overpromising.

Not as a connector. SleekAI is a chatbot that reads WordPress data, not an LMS plug-in. But it can describe which export formats your programs support (SCORM 1.2, SCORM 2004, xAPI, completion data via API) and which client LMS platforms you have delivered into. For buyers whose LMS is the deciding factor, this honest scoping in chat saves a week of vendor calls.

Yes. Display conditions let you switch the bot on or off by URL, date, or specific landing pages. During end-of-quarter when sales bandwidth is constrained, you can scope the bot only to evergreen program pages and disable it on time-sensitive RFP landing pages. Date-based rules avoid the need for a manual toggle, which is useful for global firms where 'end of quarter' has different timing per region.

Inside your WordPress database. Each log row stores the model used, token usage, the page URL, and the full conversation. Revenue ops can audit which programs draw the most chat traffic and which questions stall buyers. For enterprise clients with strict data residency or NDA requirements, in-database logs are a meaningful advantage over hosted chatbot services that store transcripts on their own infrastructure.