Yes. SleekAI reads your taxonomies (categories, tags, custom taxonomies) and ACF or postmeta fields, so the bot understands persona, funnel stage, format, and topic in whatever structure you already have. You do not need to reorganize your library. If your tagging is sparse, the bot still works off title and summary, but rich tagging gives sharper matches because the intent-to-asset mapping has more signal.

Yes. The bot can recommend a gated asset (whitepaper, advanced template) and route the visitor to the matching form rather than trying to surface a direct file URL that would defeat the gate. The recommendation includes the asset summary so the visitor knows what they are filling the form out for, which usually lifts gate completion compared to a static library tile.

Yes. Many libraries split content across CPTs (one for guides, one for templates, one for videos, one for case studies). SleekAI's data-source wizard reads all of them and surfaces results across types in the same conversation. That avoids the trap where a single search only looks at one CPT and the visitor walks away thinking the asset they want doesn't exist.

Yes, if your library tags resources by persona (founder, marketer, engineer, ops) or by funnel stage (awareness, evaluation, post-purchase). The bot picks up cues from the conversation about who the visitor is and prefers assets matching that persona or stage. For libraries that don't tag this way, the bot still works but the matches are less personalized.

The model itself does not retrain on your data. What improves is the system prompt and the asset tagging based on what conversation logs reveal. Teams typically see clusters of queries that the bot answered poorly because the underlying asset was untagged or buried; tightening the tagging and the recommended-link policy in the system prompt makes the bot sharper without any AI training step.

Yes. SleekAI supports multibot, so a B2B SaaS marketing site can run one bot for the founder hub, one for the marketer hub, one for the engineering hub, each scoped to that audience's resources. The system prompt for each is tighter and the recommendations more relevant than a single catch-all bot for the whole library.

SleekAI is a one-time WordPress plugin license. You bring your own OpenAI or Anthropic API key, so usage cost is just tokens - typically a few cents per conversation, which on a content library that gets thousands of visits a month works out to far less than a per-library SaaS recommendation engine that charges by traffic tier.

Conversation logs surface the gaps. A pattern of 'how do I do X' questions with no matching asset is your content team's most useful brief. Many teams treat the log as a backlog: the highest-frequency unmatched query gets commissioned next, and after the asset ships the bot starts surfacing it immediately because the library is its only source of truth.