AI 智能体1 week ago
EaseClaw: Find warm B2B buyers where they're already asking
在12个来源发现B2B买家，按购买意向排名，自动生成回复。
@MannPriteshh · X
Checkout it helps businesses find leads easily
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在12个来源发现B2B买家，按购买意向排名，自动生成回复。
@MannPriteshh · X
Checkout it helps businesses find leads easily
与AI买家进行冷电话练习，提升销售技能和求职竞争力。
@elliottships · X
Building AI-led sales coaching with real-time cold calling practices
发现包含需求信号和竞争分析的商业机遇。
@businessHunter_ · X
Business Hunter scans Reddit, HN and GitHub for real demand signals → tells you exactly what to build before you write a line of code.
OutsScale：检测购买信号，获取已写好的外展文案。
@rajkvishal · X
Find buyers already showing purchase intent — before your competitors do.
发布域名需求，卖家竞价的反向拍卖市场
@namefit1 · X
How many builders have the right domain name for what they are building? makes it easy for them. You list your needs, seller bid their names, and you pick the winner. This video explains it
识别 B2B 网站访客，并根据购买意图自动化销售外展。
@visonmilan · X
Building AI Employees for B2B businesses. Recently released first AI Employee Kwin that optimizes existing traffic to generate more revenue-
浏览600+B2B营销框架，获取实战案例，优化定位和外联。
@ZofloqDev · X
It's a library hosting over 500 proven frameworks that can be filtered and matched to your exact problem. This helps with outreach, positioning and strategy going forward let me know what's good and bad about it would love the feedback
通过Google Maps抓取商业线索，快速获取公司电话、网址和邮箱。
@eskayML · X
Lead gen for dummies
在Google Maps上发现本地业务，评分潜在客户，生成个性化WhatsApp消息。
@AbosiGodwin · X
Kairo 扫描 Reddit，找到在寻找你的产品的用户，自动推送客户线索。
@Emmanuel1134541 · X
If u ain't getting users to your product try it free though
YouEx.ai 是面向 B2B 销售团队的 AI 原生 CRM 平台，自动捕获、丰富、评分和分配线索。
u/youex-ai · Reddit
Built a CRM w/ MCP -- Biggest misunderstanding on first look? We launched an MCP connector a few weeks ago that connects our CRM data. We're still working through our product market fit, so I asked Claude What is the biggest thing people misunderstand about YouEx.ai when they first see it? I was actually not even thinking about researching our actual CRM data, but that's what it did. The answer was actually really insightful: Your own data points at it: a large sha
