You talk,
we handle the rest.

Every agent call — whether placed from the mobile app, routed through a Twilio tracking number on a yard sign, or captured by a Plaud device — gets recorded, transcribed by Deepgram Nova-3, and processed by Claude.

The system extracts buyer criteria (price range, beds, square footage, area, must-haves like a shop or two masters), creates a persistent MLS search against the buyer profile, updates the contact record with everything new from the conversation, generates ranked follow-up tasks, and drafts a personalized follow-up email in the agent's voice.

All of it, in under five minutes from hang-up. The agent gets a single notification: AI processed your call with John — draft follow-up ready.

Replaces: Otter, half of your CRM workflow, most of your post-call admin.

A modern CRM purpose-built for residential real estate. AI auto-categorizes contacts by stage — early buyer, active buyer, under contract, seller, past client, referral source — and scores them by actual revenue potential, not vanity engagement.

The system continuously deduplicates and cleans as new data flows in. New contacts created from call transcripts get matched against existing records and merged with audit-traced confidence scores. Dead contacts are flagged, not deleted — you decide what stays.

Migration from Follow Up Boss is included in onboarding: contacts, tags, notes, deal stages, full history. We run AI dedup on import with less than 2% false-positive merge rate.

Replaces: Follow Up Boss.

Outreach that references what was actually said. Not template variables filled in — real content from the call.

“Hey Sarah, that three-bed on Elm with the shop you mentioned — something just hit the market in the Snake River area that's close. Two masters, three-quarter acre. Want me to send the listing?”

The AI manages segmentation, cadence, and timing per contact — not by a generic drip schedule. Sequences pause on reply. The daily hot list ranks who to call by revenue potential and engagement signal, not by last-touched-date.

Each email comes in as a draft for one-tap agent approval. Or you can let the AI send automatically — the graduated autonomy dial in the Permission Evolution settings is per-module, per-agent.

Replaces: ylopo AI drips, your manual sequence work, the guilt about not following up.

Real estate teams in Idaho service three to four MLS boards simultaneously — Teton, Snake River, Paragon, Soda Springs/Preston. Most agents search them one at a time and re-key buyer criteria between systems.

Rize OS integrates with all of them via Trestle (CoreLogic's RESO Web API). Buyer profiles extracted from call transcripts become persistent smart searches across every connected board. When a new listing hits any board, AI evaluates fit and produces a confidence score against every active buyer profile.

92% match for Sarah Thompson — $700K, shop, two masters, Teton County.

High-confidence matches (above 85%) trigger an immediate push notification to the assigned agent. One tap to forward the listing with personalized context.

Replaces: the spreadsheet of saved searches you maintain manually, the missed opportunities when a listing lands and nobody catches it.

Residential real estate teams lose $15,000 to $50,000 a year per team to missed deadlines — because contingency periods get tracked in personal Google Calendars no one looks at.

Rize OS reads the executed contract — PDF or image upload — and extracts every date, contingency period, and deadline. Calculates business days minus federal and state holidays. Builds the full transaction timeline. Posts it to the team calendar automatically. Generates the post-acceptance checklist (inspection scheduling, appraisal, title, HOA, insurance) with per-role reminders.

Milestones check themselves off when confirmation emails arrive. Vendor requests are tracked. Nothing falls through.

Replaces: your TC's spreadsheet, the personal calendars no one looks at, the $15K–$50K per year per team in missed deadlines.

CC&Rs, plat maps, covenants, vendor lists — all indexed during onboarding with pgvector embeddings. Searchable in natural language.

A buyer asks whether a particular parcel allows detached shops. Three seconds later: Section 4.2 — detached shops up to 1,200 sqft permitted with HOA approval. With a clickable reference to the source document.

Missing-doc detection runs across active transactions. If the HOA disclosure isn't in the file, Rize drafts a request to the listing agent automatically — for your approval before send.

Replaces: Dropbox digging, the embarrassment of telling a buyer you'll get back to them on a covenant question.

Running comps takes 60 to 90 minutes today using Cloud CMA. Rize OS does it in under ten — and it does it the way you would.

During onboarding, each agent records a 30-minute screen-share walking through how they run comps: which comparables they pull, which adjustments they make, which finishes matter, how they weight recency. The AI trains against that methodology. Your CMAs come out looking like your CMAs — not a generic model's interpretation of your market.

Pulls live MLS data via Trestle. Generates a branded report. First five AI-generated CMAs typically match the agent's hand-run CMAs within 3–5% on final value range.

Replaces: Cloud CMA. And the 60 minutes you spent on it.

Replaces the six tabs you currently have open. Today's priority tasks (AI-ranked by revenue impact). Active transaction pipeline. Smart match alerts. Lead source performance (Zillow, Redfin, sign calls, website, referral). Team activity — who's working what. Overdue follow-ups flagged in deep amber.

And the live AI Activity Feed — every action the system is taking on your team's behalf, rendered in real time. Transcribing call from Carie. Drafting follow-up to Hartwell. Matching new Teton listing to Sarah Thompson. Catching deadline for Wilson transaction.

This is the screen Dakri and Melissa start their day on. It's the screen we built for ourselves.

Replaces: SISU, six open browser tabs, and the feeling that you might be missing something.

Every listing in the pipeline gets a command board. Pre-listing tasks, photographer scheduling, MLS data entry, marketing collateral, open-house calendar, showing feedback aggregation, price-position alerts when the comp set moves.

Seller updates write themselves. Showings happened, here's the feedback, here's how we're positioned, here's the recommendation. Drafted weekly. One-tap approval before send.

Built for brokerages that take listings seriously — and want the seller experience to feel as engineered as the buyer experience.

Replaces: the listing checklist in your TC's head, the weekly seller email no one writes.

Closed volume, GCI, average price point, days-to-close, conversion by lead source, per-agent production rank, splits and caps tracked in real time. Forecast based on the pipeline the AI actually sees — not the deals agents remembered to log.

Brokerage-wide rollups. Team-level views. Per-agent scorecards. Exportable to the formats your accountant already uses.

Designed for owners who want to run the brokerage the way Wall Street runs a desk.

Replaces: SISU, the production spreadsheet you update on Sundays, the forecast you guess at.