Yes. Each room is a sub post under its parent house with an available from date, a price, a size in square feet, a floor, and a private or shared bathroom tag. The bot reads the room posts on every request and returns the rooms opening in the next 60 days that match the applicant's budget. If a room is reserved mid conversation, the next message reflects it.

Each house has a culture note written by the community manager and stored as postmeta. The bot quotes the note in the applicant's language, with house specific examples like Sunday dinner attendance, the typical day pattern, and the noise expectation. Two houses in the same city read as two different places because the bot pulls from two different notes.

Yes. The community guidelines document for each house lives in an OpenAI Files vector store. Guest policy, pet policy, quiet hours, and shared kitchen etiquette are quoted from the right document per house. A house that allows 3 nights per month for guests gets that number; a no overnight guest house gets that. The bot never blends two houses' rules.

Display conditions scope the bot by URL pattern, login role, and applicant stage. The public house pages run a prospect bot focused on culture and availability. The /apply/ flow runs a bot that helps with the application. The /portal/ for accepted members focuses on move in, Slack, and the chore wheel. 28+ targeting rules cover the edge cases.

Each house has shared logistics fields: package locker location, visitor sign in policy, parking availability, and bike storage. The bot reads them per house and quotes them in context. A new member asking where Amazon drops packages at Maple House gets the locker location, not a generic answer about checking with the property manager.

When no room matches the applicant's window, the bot logs the request through SleekAI Agent Mode into a waitlist post type with the contact, the houses they liked, and the earliest move in. The community manager sees a clean waitlist queue, and when a room opens, an Agent Mode task can match it before going public.

All conversation logs stay inside your WordPress database. The data path is browser to WordPress to your OpenAI or Anthropic key directly, with no Sleek server in between. For member privacy this matters because the bot can quote roommates' first names, schedules, and house specifics without the data passing through a vendor. Retention is configurable in admin.

Single family chatbots have one tenant per unit and no shared spaces. Co-living is the inverse: shared spaces, member dynamics, house culture, and a community manager who is half operations and half host. SleekAI reads the fields that match a co-living shape and runs different bots per house, so applicants self select and members get house specific answers.