Yes in most jurisdictions, with two cautions. First, do not ask any protected-class questions (family status, religion, national origin, disability, age unless asking for over 18). The system prompt should explicitly forbid those, and the prompt is reviewable. Second, the criteria you do apply (3x income, no smokers, pet rules) must be applied consistently and documented. The conversation log is your audit trail. Check your local fair-housing rules, in some states source-of-income is a protected class.

Per listing. If listings live as a custom post type with fields like rent, deposit, pet_policy, available_date, and income_multiplier in postmeta, SleekAI maps those into prompt variables. The bot reads the right values for whatever page the conversation started on. URL-pattern display conditions can also pin a bot to /listings/* with the active listing ID injected.

Configurable. Most teams write to a custom post type like 'rental_application' with the captured fields as postmeta, or to a Forminator form entry if they prefer that pipeline. Either way the data is in WordPress, queryable, and exportable. Add a notification action to email the property manager or post to Slack when a qualified applicant completes the conversation.

Two patterns work. The polite handoff says 'This unit does not match your situation, here are three other listings that do' with links pulled from your active listings query. The waitlist captures their criteria and notifies them when a matching unit appears. Both feel less brutal than a flat 'no' and turn a near-miss into a future lead. Never tell the applicant which specific criterion disqualified them in a discriminatory framing.

Yes. Add a branch in the system prompt: if applicant's income is below threshold but they mention a co-signer with income above 5x rent, qualify them conditional on co-signer documentation. The bot asks for the co-signer's relationship, income, and willingness to sign. Student housing especially relies on this branch.

The bot does math correctly (income / rent) and applies the threshold consistently. It does not verify the income. The conversation captures a self-reported number and the threshold pass-fail is a first filter only. Document verification (pay stubs, employer letter) happens after the showing as part of the formal application, exactly as it would today, just on a smaller pool of pre-qualified applicants.

Some will. The bot is a filter not a verifier, and any applicant willing to lie about income on a chat will also lie on the application form. The point is to remove the 80% of inquiries that are honestly mismatched (wrong budget, wrong move-in date, pets the unit does not allow). For the remaining 20%, document verification is the actual gate. The bot saves you time on the easy filtering, not on the underwriting.

Residential is the primary fit. Commercial inquiries involve very different criteria (use, build-out budget, term length, percentage rent for retail) and usually a broker on both sides. A separate commercial-leasing bot with a different prompt can work for inquiries on small office or retail spaces but the conversation pattern is closer to lead qualification than pre-screening. Use multibot to keep the residential and commercial flows separate.