Pre-scan listing descriptions, buyer and seller email sequences, neighborhood guides, market reports, and open-house follow-ups before they hit MLS, Zillow, Realtor.com, Redfin, or your client inbox. Sentence-level highlights surface the templated openers, generic neighborhood descriptors, and stock urgency lines that read AI-shaped to a buyer comparing five agents. Built for solo agents, two-person teams, and brokerages running shared listing pipelines. Free to try. No card.
Solo agents working a personal book, two-person teams splitting buyer and listing sides, and brokerages with five or more agents publishing to MLS, Zillow, Realtor.com, and Redfin share the same problem: AI-drafted copy that looks templated next to the listing one block over erodes client trust before the first showing.
Listing descriptions on the major platforms are increasingly compared for AI patterns. Buyers screenshot side-by-side openers when three descriptions on your profile open the same way, and a brokerage with twenty agents pushing AI-flavored neighborhood pages reads as a single voice across the entire roster. The realistic 2026 workflow uses AI assistance and pre-scans the output before it hits the public feed.
Listing five to thirty properties a year, running personal buyer and seller email funnels, publishing neighborhood pages on a personal site. Pro at $14.99 a month yearly gives unlimited scans, 10,000 character pastes (enough to fit a long neighborhood guide in one go), and 90-day history covering the typical listing cycle. The integrated AI rewriter handles the stubborn paragraphs that flag every time without forcing a rewrite of a description that already works.
Two-person teams splitting buyer and listing sides, or a lead agent reviewing copy from two or three associates before publication. Pre-scanning every listing before the team lead signs off cuts the review loop and keeps a defensible record per listing. The Pro tier covers most two-person teams comfortably; Business is right when the team grows past three agents or starts running shared neighborhood-page pipelines.
Five to thirty agents shipping listings, neighborhood guides, market reports, and drip sequences across multiple regions. Business at $29.99 a month yearly unlocks five seats with shared scan history, REST API access for batch pre-publish review, an audit log visible to the broker of record, and white-label PDFs branded to the brokerage. Brokerages running a minimum Authenticity Score policy on every listing usually settle on Business inside their first quarter.
A listing description on MLS that flows through to Zillow, Realtor.com, and Redfin is read by buyers across all four surfaces. Each platform has its own visual context, but the prose is the same prose, and pattern-matching across an agent's roster is happening on every surface.
Most boards do not auto-detect AI, but board rules against misleading or unverifiable claims still apply, and AI drafts routinely invent features that are not in the home. The pre-publish scan does double duty: sentence highlights expose the templated phrasing, and a human pass on the flagged lines is also the moment to catch invented hardwood floors, fictional renovation years, or non-existent appliance brands before the listing goes live.
Once a description syndicates out from MLS, it is the durable artifact buyers see. A buyer comparing five agents on Zillow reads five descriptions in a row, and the templated ones flag instantly. The pattern is easiest to spot on agent profiles where the same opener (Welcome to this stunning, Nestled in the heart of, Step into this beautifully appointed) repeats across every listing.
Redfin agents have a profile page with biography, market commentary, and a feed of recent listings. The biography and the listings are read together, so an AI-drafted profile paired with AI-drafted listings is the worst-case pattern. Pre-scanning the agent biography once and then every new listing against a 75 floor keeps the agent profile reading like a person.
Spoken scripts for listing videos and virtual tour voiceovers score well when they preserve spoken cadence (contractions, sentence fragments, conversational pacing) and score poorly when they slip into written-prose rhythm. Healthy scores on a script written from a real walk-through run 75 to 90. A script generated from listing photos alone tends to land in the templated band.
Pro at $19.99 a month standard, $14.99 a month on yearly, fits solo agents and two-person teams. Business at $39.99 a month standard, $29.99 a month on yearly, fits team leads and brokerages with five or more agents. Full details on the pricing page.
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Homebuyers and sellers in 2026 read three to five agents before they pick one. They land on Zillow, scroll an agent profile, read the recent listings, and form a snap judgment. The agents whose descriptions read AI-shaped lose the call before the phone rings.
The trust signal is not a single AI flag on a single listing. It is the pattern across an agent's roster. When three consecutive listings open the same way and use the same neighborhood adjectives, buyers conclude the agent does not actually walk the properties. Sellers conclude their listing will get the same templated treatment. The pre-publish scan is the discipline that breaks the pattern.
The most common buyer behavior in 2026 is to screenshot two or three listing openers from the same agent and compare them. If the first sentences are structurally identical (Welcome to this, Step into this, Discover this), the buyer concludes the prose was generated and the trust gap opens. Sentence highlights flag exactly the openers that produce this comparison risk.
A pre-listing conversation now routinely includes a seller asking whether the agent will write the description personally or paste it from a tool. The honest answer in 2026 is that AI assistance is normal, but the description still goes through a human-voice pass and a pre-publish scan. Showing a seller a scan report from a previous listing converts that answer from defensive to credible.
The follow-up email after an open house is the highest-stakes piece of post-visit copy. A templated thank-you opens with "It was a pleasure meeting you" and lands in the trash. A scan-checked follow-up with a specific detail from the conversation lands a reply. The Authenticity Score above 75 floor on follow-ups correlates with a meaningful lift in response rate.
The long-tail of agent business is referral. The referral source is usually a past client who remembers the agent's voice. Voice survives only when the writing is the agent's. Pre-scanning every piece of client-facing copy is the discipline that keeps the voice on the page and the referrals coming.
AI-generated listing descriptions can introduce inadvertent Fair Housing violations because LLMs default to phrasing about neighborhood character, family suitability, walkability, and school quality that maps onto protected classes. The pre-publish scan is not a Fair Housing audit, but it surfaces the templated descriptors that most often carry that risk.
AI drafts gravitate to vibrant community, family-friendly, established neighborhood, and quiet residential street. Some of these phrases are legally fraught when they imply preferences for a protected class (familial status, in particular). Sentence highlights expose the generic descriptors so the agent can swap to neutral language (close to parks, near schools, sidewalk-lined streets) that conveys the same information without the compliance risk.
Specific school ratings ("top-rated schools") and walkability claims can become Fair Housing issues depending on the market and the wording. The safer phrasing references specific public information (assigned school district, named elementary, Walk Score of X) rather than evaluative claims. The scan flags the evaluative passages so the human reviewer can either substantiate them with a specific number or swap them for neutral references.
TextSight is not a Fair Housing audit and does not replace your broker's standard checklist. What the scan does is expose the AI-shaped passages that disproportionately carry compliance risk, so the human reviewer's attention lands on the right paragraphs first. A pre-publish scan followed by a checklist pass is the workflow most brokerages settle into through 2025 and 2026.
The audit log on the Business tier shows which agent scanned which listing, with timestamps, and which descriptions were exported as PDFs before MLS submission. Useful for brokers running quarterly compliance reviews who want to demonstrate consistent pre-publish review across the roster rather than relying on individual agent judgment.
A listing description is three pieces of writing wrapped in one paragraph: the property, the neighborhood, and the lifestyle. Each piece has its own AI failure mode and its own fix. Reading the score in context of which slot is dragging beats chasing the headline number.
The property slot is where invented features show up most. AI drafts will confidently describe hardwood floors that are laminate, granite that is quartz, or a renovation year that is wrong by a decade. Sentence highlights expose the templated parallel cadence (three-bedroom, two-bathroom, single-story) and the moment the description drifts from observed detail to generated detail. Healthy property slots score 75 to 90 when written from a real walk-through.
The neighborhood slot is where Fair Housing risk concentrates and where AI defaults to generic descriptors. Replace "vibrant community" with a specific named coffee shop, "tree-lined streets" with the actual cross streets, "family-friendly" with the specific park or library nearby. The discipline of pulling specific local references into the draft lifts both the Authenticity Score and the listing's usefulness to a buyer who has never visited the area.
The lifestyle slot is the easiest to rewrite and the easiest to flatten with AI. Generic "perfect for entertaining" and "ideal for the modern family" run low on both score and conversion. Specific lifestyle hooks (morning coffee on the south-facing patio, dinner on the back deck under the existing pergola) read human because they describe a moment a person could have rather than a category a buyer might fit.
The recurring offending listing openers are Welcome to, Step into, Discover, Nestled in, Introducing, and Behold. They flag in headline scans because they sit in the templated band of LLM defaults on listing prompts. Healthier openers lead with the specific (the address, a verbatim feature the seller flagged, a moment from the walk-through). The discipline is to write the opener last, after the property and neighborhood slots are settled.
Cold outreach to sellers and nurture drip to buyers are the highest-volume copy most agents ship in a year. They are also the most templated. Pre-scanning the sequence as a batch catches the openers and subject lines that drift into the AI band before they tank reply rates.
Seller cold-open emails default to I noticed your home on, I hope this email finds you well, and Would you be interested in selling. The first three lines are the highest-AI-risk slot in a real estate cold email because they default to templated curiosity and stock urgency. Scan the full sequence (five to seven emails) as one paste rather than scoring one email at a time, and target an Authenticity Score above 75 on the openers.
Buyer drip sequences for new prospects, market-update subscribers, and former clients run ten to thirty emails over a year. Templated nurture drift is the failure mode: each email looks fine on its own, but reading three in a row reveals the same opener, the same parallel three-bullet structure, and the same generic CTA. Scan the full sequence as a batch and rewrite the recurring patterns.
Post-visit follow-up emails are the highest-converting piece of post-event copy in the agent toolkit and the easiest to flatten with a templated thank-you. The fix is concrete reference: a specific room the visitor commented on, a question they asked, the exact time-of-day they came. Scan-checked follow-ups with these specifics correlate with a meaningful lift in reply rate over generic thank-yous.
Broadcast emails announcing a new listing to the agent's full database are read by clients who already know the agent's voice. A templated broadcast erodes voice fastest because the recipients have a baseline to compare against. Pre-scanning the broadcast against a 75 floor protects the voice that built the database in the first place.
More for real estate teams.
Ad copy, sales pages, and email sequences. The pre-handoff scan ritual translates directly.
For copywriters →Neighborhood pages and area guides are SEO assets. How agency teams build pre-publish review.
For agencies →Light, Balanced, and Maximum modes for rewriting listing openers and email subjects without losing voice.
Read the guide →Free, Starter, Pro, Business. Yearly billing saves 25%. Solo agent to brokerage tiers.
See pricing →Free to try. No card. Pro at $14.99 a month on yearly for solo agents and small teams; Business at $29.99 a month on yearly for brokerages with five or more agents.