Hundreds of inquiries about one property. Most of them, with no real intent to buy.
The best real estate agent, cloned — qualifies, nurtures, and books the showing, so the sales team only talks to whoever's ready to close.
Every task in each inquiry, handled with AI.
Most inquiries never convert — the volume is noise, not signal. Filtering it by hand is where the best agents' time gets wasted.
Property details
Answers price, size, amenities, and location questions from the listings — reads a floor plan to explain the layout, and searches by proximity to a point on the map.
Lead qualification
Scores budget and intent from the first exchange, so agents spend time on leads that convert.
Showing scheduling
Books a property showing directly on the right agent's calendar.
Cold lead follow-up
Re-engages leads that went cold, with the right cadence, without chasing them by hand.
Required documentation
Explains what paperwork is needed for a purchase or a lease.
Financing questions
Answers the basics of mortgage credit consistently, every time.
CRM logging
Logs every qualified lead and every conversation in the CRM automatically.
Handoff to an agent
Passes a hot lead to a human agent with full context at exactly the right moment.
It's not another lead-gen widget. The best agent, cloned.
Most real estate bots just answer a scripted FAQ. We start from the person on the team who already qualifies leads well, and clone the entire conversation — inbound and outbound.
Trained on the team's real playbook, not a script.
We capture how the best agent actually qualifies a lead and books a showing — tone included.
Covers both directions of the funnel.
Answers inbound inquiries and runs outbound prospecting and qualification at scale — the same deployment Mudafy runs today.
Every task handled with AI, on every channel where people already look for a home.
WhatsApp, Instagram, email, and web chat — the same assistant, the same context, on whichever channel the lead is already using.
Security at every layer, from the model to the client's data.
LLM security, agent security, client control, and infrastructure aren't the same layer — each protects something different, and the agent leaves a trail of everything it does along the way.
A protective layer around the model.
A language model can make the wrong call — delete something it shouldn't, invent data that doesn't exist (like a bank account number), or let spend spiral out of control. Guardrails validate what the agent is about to answer before it answers, automatically or manually, covering hallucinations and prompt injection.
The same guardrail running in production, available to test.
We can host the guardrail we use today so your security team can test it directly, instead of taking our word for it.
The model never sees another user's data.
The logic that decides what information to bring into each conversation lives in code, not in the model — it's not a guardrail, it's the default architecture. A deterministic agent can't cross data between users or reach beyond what belongs to that conversation.
The client decides what information reaches StudioChat.
Every integration goes through a middleware layer the client configures — StudioChat can't see the data the client chooses not to share. Control stays on the client's side, by design.
The standards you'd expect from a cloud platform.
Encryption in transit and at rest, retention configurable by the client, two-factor authentication for every user, and full traceability of every change made to an assistant — versioned, with a record of who did it.
The agent explains what it does, why, and where each fact comes from.
The most common fear is that the agent does something and no one finds out. That's why every answer comes with its reasoning and its citations — no black box acting without leaving a trace.
"An outbound assistant that contacts and qualifies real estate leads at scale — booking the right conversations for the sales team."
What a real estate team actually asks.
What exactly does the assistant handle?
Property questions, lead qualification, showing scheduling, cold lead follow-up, documentation requirements, financing questions, CRM logging, and handoff to a human agent.
Can it read a floor plan or search properties by location on a map?
Yes. The assistant can interpret a floor plan to explain the room layout, the size of each space, or whether a piece of furniture will fit in a room — and it can also read an address or a point on the map to answer queries like 'an apartment near Plaza Italia', matching against each property's real location.
Does it work for outbound prospecting, not just answering inbound?
Yes — outbound prospecting and qualification at scale is Mudafy's real deployment, alongside answering inbound WhatsApp inquiries.
Does it replace our CRM?
No. It logs every qualified lead and every conversation in whichever CRM is already in use, as a non-human agent.
How is it priced?
Outcome-based: priced per qualified lead or resolved inquiry, not per seat, not for setup.
Do you have a reference client in real estate?
Yes — Mudafy, a LatAm proptech, qualifies hundreds of real estate inquiries a month with a StudioChat assistant, booking the right conversations for its sales team.