Placy Pro vs CRMs
How to select the best solution for your real estate team?
Placy Pro is purpose-built for real estate — it ships with industry workflows, utilizes industrial data, native integrations and voice/text AI, and 50+ language support. That means accurate, context-rich conversations and 24/7 workflows out of the box — no heavy customization or long engineering projects.
Operationally, Placy automates qualification, sends branded follow-ups, and syncs cleanly into your CRM so agents only get sales-ready prospects. Faster onboarding, lower TCO, and immediate lift in lead response let teams sell more while doing less.
Pre-Built for Real Estate
The entire system is designed around real estate concepts (leads, listings, transactions). The AI understands industry context and conversations out of the box.
Generic System
The CRM and its AI are blank slates. You must invest significant time and effort to configure and "teach" them the specifics of a real estate workflow and vocabulary.
Native Conversational AI
Core features include inbound/outbound AI phone calls, lifelike voices, and omnichannel chat (WhatsApp, etc.). It acts as an autonomous agent for your team.
Not a Core Feature
CRMs lack native, autonomous conversational AI. Achieving this requires complex, costly integrations with separate third-party voice and chat platforms, which you then have to manage.
Fully Managed Service
All platform updates, workflow maintenance, and AI model optimizations are handled for you by a team of experts, ensuring the system stays effective.
Significant Internal Burden
Your team is fully responsible for maintaining the custom workflows. When the CRM or its APIs update, your automations can break, creating an ongoing technical liability.
Fast & Turnkey
As a managed service, it's designed to be implemented quickly. You are configuring a proven system, not building a new one, leading to a rapid return on investment.
Slow & Resource-Intensive
This is a major internal project. It requires extensive setup, workflow building, testing, and AI prompt engineering, which can take months to deliver value.
AI-first strategy
Multi-model, task-specific strategies, advanced prompt and context engineering, RAG implementation, AI evaluations, and human-in-the-loop systems.
Old achitecture
CRMs add LLM features with single-model GPT-style integrations or vendor ML; Multi-model setups are rare and require custom engineering.
Deep branding and customization
Rich customization: visual persona, tone/phrase controls, and the ability to clone or select professional voices so the assistant sounds like your brand or even a team member.
Limited
Basic branding (bot name/avatar, canned tone) is common, but deep persona control and production-grade voice cloning are rare or require third-party tooling
