AI Call Review and CRM for Real Estate Brokerages and Teams
For brokerages and real estate teams: AI reviews every buyer and seller call, turns promised showings into tasks and keeps lead history with the team.
A real estate deal runs for weeks or months: a call about a listing, a buyer consultation, several showings, an offer, inspection, closing. Along the way the client talks to the agent many times, and everything that matters — budget, pre-approval, doubts, what was promised — is said on those calls, not typed into the CRM. The broker sees “showed three homes, client is thinking” and has no idea how each agent handles the moments that decide the deal.
The start matters just as much. A buyer who asks about a listing usually reaches out to more than one agent, and the one who calls back first — and asks the right questions — tends to get the appointment.
Where leads and deals get lost
- Slow response to new leads. A listing inquiry sits for two hours; by then the buyer has booked a showing with whoever called first.
- Lead calls without qualifying. The agent talks about the house for fifteen minutes and never asks about pre-approval, timeline or whether the buyer already has an agent — then spends Saturday showing homes to someone who can’t buy for a year.
- The house didn’t fit, so the call ended. “That one’s already under contract” — and goodbye, instead of offering similar listings.
- Silence after the showing. Nobody set the next contact with a date, and the buyer writes an offer with another agent.
- “We’re looking next spring.” The agent promises to call in March, and March comes and goes.
- Pushback met with a concession. A seller wants a higher list price or a lower fee, and the agent gives in on the spot instead of walking through comps and the marketing plan.
- History that leaves with the agent. Calls on a personal cell, emails in a personal inbox — when the agent leaves the team, the pipeline leaves too.
How Omniscore handles it
Omniscore connects to your phone system through its API or an SFTP folder (or you upload recordings) and to the team’s mailboxes over IMAP. Agents keep their numbers, and every conversation goes through the same steps:
- Every call reviewed. About two minutes after the call: a transcript with speakers and timestamps, a score against your checklist with a quote for every point, a summary, the outcome and the next step. See the AI call analysis page for how it works.
- Showings, call by call. Set a booked showing as the goal of a call, and the dashboard shows what share of calls about a property ended with one. A call where the showing was lost on the agent’s side — no other home or time offered — stays on the Today screen until someone reaches the client.
- The conversation finds its deal. AI links calls and emails to the client’s deal in the CRM. If the client has more than one — say, they’re selling a condo and buying a house — and AI isn’t sure, the call goes to the “Review” queue, and the agent picks the deal.
- Promises become tasks. “Showing Saturday at 11,” “I’ll call you when the seller responds,” “I’ll check in with you in March” — AI creates a task with a due date. Overdue ones turn red.
- Separate pipelines for buyers, sellers and rentals. For buyers, for example: new lead → qualified → showing scheduled → showing done → offer → under contract → closed. Each stage gets an SLA, so a deal that sits too long is highlighted, and lost deals close with a reason from a fixed list: “bought with another agent,” “not pre-approved,” “priced out,” “postponed.”
- Email next to calls. Client emails sit in the same timeline as their calls, the Today screen shows who has been waiting for a reply and for how long, and new inquiries can go to agents on shift, in rotation or by workload.
- The whole deal in one answer. Ask Omni “What did we hear on calls about this deal?” and get a summary of every call with dates and links: what the client asked, what the agent promised and what actually decides the deal. Omni can suggest a note for the deal but never changes anything on its own.
Scorecard for a buyer lead call
| Criterion | What AI checks |
|---|---|
| Introduction and listing | Gave their name and the team’s and confirmed which property the call is about |
| Timeline and motivation | When they want to move and why: a new job, a growing family, a lease ending |
| Budget and financing | Price range, and whether they’re pre-approved, paying cash or need to sell first |
| Other agents | Asked whether they’re already working with an agent |
| Alternatives | If the home is under contract or doesn’t fit, offered similar listings instead of ending the call |
| Buyer agreement | Before the first showing, explained how the team works with buyers and what the written agreement covers |
| Price objections | On “it’s overpriced” or “will the seller take less?”, asked what they’re comparing it with and answered with facts, not promises |
| Next step | A showing or a call with a date and time |
| Critical | False information about a property or its price, a promise made on the seller’s behalf, or steering comments about who lives in a neighborhood |
Seller calls get their own items — motivation, timeline, price expectations and how the agent answers “another agent will do it for less.” Each item can have a rule for when it applies, so a buyer call isn’t graded on listing questions. If your team splits inside sales agents and listing agents, each group can have its own scorecard. Every score comes with a quote from the call, so the broker sees the agent’s actual words, not an abstract “didn’t handle the objection.”
What the broker or team lead sees
- Agent leaderboard — score, critical fails, unreturned missed calls and the trend for every agent. Sort by “Needs attention” to see who to talk to first.
- Standards compliance by item — who skips qualifying, who gives in on price and how often calls end with a showing or a call on a set date.
- Pipeline report — how many deals move from showing to offer to under contract, how long they sit in each stage and which ones are past SLA.
- Overdue tasks — showings and callbacks that were promised and forgotten.
- Morning questions for Omni — “Who haven’t we called back?”, “Which deals are stuck past SLA?” You can ask the same from your own ChatGPT or Claude through the Omniscore MCP connector.
Pricing and pilot
The Omni core is $149 a month per workspace for a team of up to 10 agents; each additional 5 agents is $59 a month. The CRM with pipelines for buyers, sellers and rentals is $79 a month, Email is $15 and Tasks $25. A separate office or brand with its own team and reports is another $19 a month. AI review is billed from a prepaid balance as you go — about 2¢ for a 1–2 minute call. Prices exclude sales tax. Build your setup in the calculator on the homepage; the details are on the pricing page.
The pilot runs for 14 days on your real calls and email, with every module: up to 1,000 minutes, no prepayment and no contract. We connect your phone system and mailboxes, set up your checklist and pipelines, and check the AI’s scores against yours on 20–30 calls. Within 3–5 days you’ll see who isn’t qualifying leads, who gives in on price and which clients haven’t been called back. Request a pilot.