AI Compliance & Risk · Residential Real Estate
MHRealtyAI reads the agreements, disclosures, listings, and agent messages your brokerage already produces — and reviews the actual language against state-specific rules. Not just "is it signed," but "is it right."
Decision-support, not legal advice — a licensed human always makes the final call.
Why now
Three regulatory shifts created durable, recurring compliance demand. The exposure is real, it's language-level, and it varies by state.
The gap
Transaction platforms confirm a document is present, signed, and filed. Almost none review whether a clause actually meets the legal standard for the state. That semantic gap is exactly where the liability — and the budget — concentrates.
Post-settlement buyer-agreement and compensation-disclosure requirements vary by state and MLS, and phase in through 2026. A human reviewer can't keep current.
The costliest Fair Housing failures aren't in polished listings — they're in the hurried text, the showing remark, the email. And everyone screenshots.
Managing brokers review every file page-by-page against state rules — slow, inconsistent, and personally on the hook for what they miss.
Free Compliance Check
A live taste of Modules A & B. Every finding cites the exact offending text, the rule it implicates, the authority, and a suggested compliant rewrite — the same grounded output that drives the full platform.
Custom text detected — this live demo flags a curated set of example patterns, not the full state rule set. The complete platform reviews every rule.
Try editing the text — remove "TBD" or "St. Mary's Church" and re-run to watch findings clear.
The platform
Not another transaction platform, and not just a Fair Housing scanner — the integrated layer that reviews the actual language, end to end, and proves your process.
Clause-level review against post-settlement, state-specific rules. Detects open-ended compensation (ranges, "TBD," "whatever the seller offers"), missing "fees are negotiable" statements, wrong or outdated form versions, and inconsistent signatures or dates.
Scans listing copy and agent emails & texts for coded, discriminatory, steering and proxy language — where the costliest violations actually happen — and suggests compliant rewrites, accounting for state-specific protected classes.
Splits and classifies a whole closing file, then checks completeness and correctness — required docs present, correct versions, fields consistent across documents.
Per-file report (text, rule, authority, fix) plus an immutable, timestamped, rule-version-stamped log. The defensible record you show a regulator or plaintiff's attorney. PDF export.
Portfolio queue with statuses and open-risk counts, filters by agent / state / type, plus recurring-issue and per-agent views — for coaching, not punishment.
How it works
A hybrid pipeline: deterministic rules handle anything mechanically checkable; an LLM is used only for genuine semantic judgment — always with the source text and the retrieved rule in context. The system cannot assert a finding it can't ground.
Upload or forward to a per-brokerage email address.
OCR + layout; label each document type; split packets.
Deterministic checks in code + semantic checks over the rule engine.
Quoted text, rule, authority, confidence, suggested rewrite.
Reviewer resolves / accepts / overrides each flag with a note.
Append-only, rule-version stamped, reproducible months later.
The moat
The reason a generic LLM wrapper can't replace us. Every rule is a structured object tied to its legal authority, carries an effective date and version, and is regression-tested before release. When a rule changes, old reports stay reproducible.
// a rule is a structured, versioned object { "id": "MHR-NAR-COMP-001", "jurisdiction": "US-FEDERAL", "docType": "buyer_rep_agreement", "description": "Compensation must be objectively ascertainable and not open-ended", "authority": "NAR settlement (2024-08-17)", "severity": "high", "method": "hybrid", "version": "2026.04", "effectiveDate": "2024-08-17" }
Honest differentiation
| Capability | Checklist / TMS SkySlope, dotloop |
Fair Housing scanners FairSentry, B.Claw |
MHRealtyAI |
|---|---|---|---|
| Clause-level correctness review | Completeness only | — | Yes |
| Fair Housing across agent comms, not just listings | — | Listings / marketing | Yes |
| Whole deal-file QA (complete + correct) | Checklist completeness | — | Yes |
| Immutable, rule-versioned audit trail | Partial | Per-asset logs | Yes |
Strategy: integrate, don't fight for the system of record. We sit on top of where files already live as the system of intelligence.
Trust & posture
We flag, explain, suggest, and log. A licensed human makes the final call. Suggested rewrites are drafts — UPL-aware by design.
Every flag cites the exact span and the rule. Retrieval over recall; confidence + abstention. A finding with no source span is suppressed.
Append-only, tamper-evident, rule-version stamped. Reproduce any past report and show exactly which rule and human action produced each finding.
Encryption in transit & at rest, strict multi-tenant isolation, RBAC, limited-retention LLM terms, and controls designed toward SOC 2.
Who it's for
Big enough to feel real liability and hold budget; small enough to buy without enterprise procurement. The broker buys and configures; agents and coordinators are the volume users whose work is reviewed.
Personally and supervisorily liable. "Make sure nothing in my agents' files creates a fine, lawsuit, or license problem — without me reading every page."
"Catch every error before close, faster — and prove I did." Cares about accuracy, throughput, clear flags, audit logs.
"Submit clean files the first time." Cares about pre-submission checks and fewer rejections.
"Don't accidentally write something non-compliant." Wants fast feedback — and not to get in trouble.
Pricing
A 50-agent brokerage runs roughly $750–2,000/month — trivially justified against one avoided Fair Housing penalty or one defended deal.
Plus a per-transaction add-on (~$10–25/file) for variable-volume buyers and coordinators. Indicative pricing — validated with design partners.
Get started
Join 5–10 design-partner brokerages shaping V1 across Texas, Florida, and New York.
Book a demo
Tell us about your brokerage and we'll set up a walkthrough. We respond within one business day.