✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount

AI chatbot for WP Realty: chat across MLS listings

SleekAI maps the WP Realty listings table, including price, bedrooms, bathrooms, square feet, and city, so visitors can ask plain English questions about your MLS inventory. Bring your own OpenAI, Anthropic, Google, or OpenRouter key.

♾️ Lifetime License available

SleekAI chatbot for WP Realty

MLS data deserves a human-sounding front door

WP Realty stores listings in a custom table rather than the WordPress posts table. That is great for performance with thousands of MLS records, but it is the reason most generic chatbots cannot help your site. They read posts and pages, they do not query wp_realty_listingsdb, and they have no idea what listingprice or bedrooms mean in your schema.

SleekAI handles this with a custom-table variable mapping. A developer writes one PHP filter that exposes the WP Realty table as a named context variable and the bot can now ask "give me the three lowest-priced 4-bed homes in Reno listed this month" and get a real answer pulled directly from the table.

For brokerages with hundreds or thousands of feed-imported listings, the value compounds. The bot can answer school district questions, walk through the difference between two similar homes, and keep the conversation flowing without paging the buyer through twelve archive pages. Generic chatbots simply cannot reach into a custom table.

Workflow

How the WP Realty bot works

1

Map the listings table

A developer adds a PHP filter that returns rows from wp_realty_listingsdb filtered by status and city. SleekAI registers that filter as a named variable the model can reference.
2

Add neighborhood knowledge

The system prompt holds your local color: schools, commutes, HOA quirks. This is the layer that turns the bot from a search box into a guide a buyer trusts.
3

Route to the right agent

When a visitor asks for a tour, the bot captures contact info and the MLS number and posts to a webhook. The buyer-side agent attached to the listing picks it up from there.
4

Iterate from the logs

Conversation logs show which MLS numbers get the most chat attention. Use that to spot listings that need better photography or a price review, not just to track lead volume.

Try it now

A typical WP Realty conversation

A relocating family explores Reno listings, compares schools, and books an in-person tour with the listing agent.

Comparison

Generic chatbot vs SleekAI for WP Realty

Generic chatbot

  • Cannot read WP Realty's custom listings database table
  • Has no concept of MLS price, status, or property type fields
  • Cannot intersect city, beds, baths, and feature filters in one turn
  • Forces buyers back to the search form when criteria change
  • Never knows when a listing moves from active to pending

SleekAI chatbot

  • Reads the wp_realty_listingsdb custom table directly
  • Maps price, beds, baths, sqft, city, and status as variables
  • Supports MLS feed updates without re-importing the bot context
  • Handles 1,000+ listing inventories without slowing chat replies
  • Logs which MLS numbers buyers ask about most often

Features

What SleekAI gives you for WP Realty

Custom table support

WP Realty stores everything outside the posts table. SleekAI's variable mapping exposes that table to the model as a named context so the bot reads real prices and bed counts on every reply, not stale snapshots.

MLS feed friendly

Listings rotate fast. The bot queries on demand instead of preloading a snapshot, so price drops and status changes show up in the next chat reply within seconds of the importer running.

Neighborhood smart

The system prompt holds your local knowledge about school districts, commute times, and HOA quirks. The bot blends that with the live MLS data so answers feel like a junior agent who knows the city.

Use cases

Where MLS-driven brokerages benefit

Relocation specialists

Out-of-state buyers ask broad geography questions before they shortlist. The bot frames neighborhoods and price bands in one turn, then narrows to specific MLS numbers in the next.

High-volume brokerages

When your feed has 2,000 active listings, no one reads page three of search results. The bot finds the right three homes from the full set every time, not just the top of the archive.

Buyer agent teams

Each listing is tied to a buyer agent in the WP Realty schema. The bot can route the conversation to the right team member when the visitor commits, with the MLS number attached.

The bigger picture

Why MLS sites need conversational search

MLS feeds are unforgiving to UX. A new buyer arrives, sets bedrooms to 3, hits search, and gets 184 results. They pick the wrong sort order, scroll for two minutes, and bounce.

The data was there but the funnel asked the buyer to be an expert before showing the inventory. A chat that reads the same MLS table flips that experience. The buyer arrives, types one sentence, and gets three homes.

They ask about schools and get a real comparison. They ask about a backyard and get a real lot size. By the time they request a tour, they have done the work of a fifteen-minute phone call without occupying a single agent minute.

Most brokerages do not think of their site as an answer machine. They think of it as a brochure with a search form bolted on. WP Realty is a great engine for that brochure-plus-search model, but it leaves a gap between the buyer's natural language and the search form's required fields.

SleekAI closes that gap. The bot does not need to know everything in the MLS. It just needs to read the active rows and write a useful sentence about three of them.

The team behind the brokerage stays the deal-makers. The bot covers the work no one wants to do, which is repeating the same five answers about Somersett schools and dog-friendly HOAs to every visitor at 11 pm.

Questions

Common questions about SleekAI for WP Realty

A developer adds a PHP filter that exposes the wp_realty_listingsdb table as a named context variable. SleekAI passes the rows to the model on each turn so answers always match the live database. The setup is about ten lines of code.

 

No. The bot only queries when a visitor asks a relevant question, and the query is filtered server-side before tokens ever hit the model. A 2,000-listing site adds about 40 ms per query, well below the model latency.

 

Yes. WP Realty stores the listing agent ID per row. SleekAI can filter by that ID via a context variable so individual agents can run their own page bots with only their inventory.

 

The variable mapping is a plain PHP array. Rename any field to match the WP Realty schema in your installation. The bot only sees the friendly names you assign, not the raw column names.

 

Yes, if you store open house dates in a related table or column. Expose them as a variable and the bot can answer "any open houses this weekend in 89523" with the correct subset.

 

Filter by the listing status column in your context query. Most brokerages limit the bot to active and coming-soon, hiding pending and sold from chat-driven search results.

 

Indirectly. The bot can quote sample monthly payments using a simple formula with the listing price, the asked-about down payment, and a rate variable you set in PHP. It will not replace a licensed loan officer.

 

Custom table queries pull only a few rows per turn, so token use stays modest. Expect 1,500 to 4,000 tokens per full conversation, which is around 1.5 cents on gpt-4o-mini. Logs show the exact per-message cost.

 

Pricing

More than 1000+
happy customers

Explore our flexible licensing options tailored to your needs. Upgrade your license anytime to access more features, or opt for a lifetime license for ongoing value, including lifetime updates and lifetime support. Our hassle-free upgrade process ensures that our platform can grow with you, starting from whichever plan you choose.

Starter

€79

EUR

per year

  • 3 websites
  • 1 year of updates
  • 1 year of support

Pro

€149

EUR

per year

  • Unlimited websites
  • 1 year of updates
  • 1 year of support

Lifetime ♾️

Most popular

€249

EUR

once

  • Unlimited websites
  • Lifetime updates
  • Lifetime support

...or get the Bundle Deal
and save €250 🎁

The Bundle (unlimited sites)

Pay once, own it forever

Elevate your WordPress site with our exclusive plugin bundle that includes all of our premium plugins in one package. Enjoy lifetime updates and lifetime support. Save significantly compared to buying plugins individually.

What’s included

  • SleekAI

  • SleekByte

  • SleekMotion

  • SleekPixel

  • SleekRank

  • SleekView