
房地产 CRM AI 助手:在经纪人沟通历史上微调跟进模型
房地产经纪人因未能跟进而失去交易。在经纪人自己的沟通历史上训练的微调模型用经纪人的声音起草个性化跟进——将关系维护从每月 6 小时减少到 45 分钟。
年收入 $200,000 和 $800,000 的经纪人之间的差别通常不是技能——而是持续跟进。微调模型使用经纪人的真实沟通,以他们的声音起草个性化消息,响应率达到 30-40%,而通用模板只有 3-5%。
输入:联系人记录(身份、关系上下文、最后互动、相关生活事件) 输出:以经纪人声音撰写的即发消息草稿
训练需要 300-800 个干净的(上下文,消息)对,来自经纪人的邮件历史、CRM 笔记和过往通信记录。
月度时间节省:从每个联系人 12 分钟降到 2 分钟(审查 + 编辑草稿),10 人团队每月收回 50 小时。
续费合理性:$300-500/月/经纪人,涵盖季度重新训练以适应新通信模式和市场条件变化。
Ship AI that runs on your users' devices.
Ertas early bird pricing starts at $14.50/mo — locked in for life. Plans for builders and agencies.
Ship AI that runs on your users' devices.
Early bird pricing starts at $14.50/mo — locked in for life. Plans for builders and agencies.
Keep reading

Real Estate Lead Qualification AI: Fine-Tune a Scoring Model on Your Conversion History
Real estate teams waste hours on low-intent leads. A fine-tuned classifier trained on your closed and dead leads automatically scores inbound leads so agents focus on the ones that close.

The Real Estate AI Agency Opportunity: High-Value Clients, Repeating Use Cases
Real estate is one of the highest-value verticals for AI agency work. Here's the specific opportunity: the use cases, the buyers, the data assets, and why real estate clients stay on retainer.

Fine-Tune a Listing Description AI for Real Estate: Step-by-Step
Real estate agents spend 30-45 minutes writing each listing. A fine-tuned model trained on the brokerage's own listings generates on-brand descriptions in 2 minutes. Here's how to build it.