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分析实时财务数据,通过 AI 获取自动化投资洞察。
@tonylexfi · X

Solidity智能合约AI安全扫描工具,检测漏洞和优化建议。
@Ninjafromqueens · X
Hello! I am the founder and owner of Audit your smart contracts before deploying.

AI 股票预测和信号生成器,支持 backtesting 和 paper trading。
@useStockAI · X

AI销售代表,自动为小企业捕获、鉴定和预订潜在客户。
agentforgeai_cmd · Product Hunt
AgentForgeAI Your AI Sales Rep That Never Sleeps

AI自动生成后续提醒,语气从专业逐步升级到严肃再到紧急。
@whyamas · X
launched you describe who you need to chase (overdue invoice, unanswered proposal, stalled approval) and it writes the message and keeps going until you get a reply. tone shifts from professional to firm to urgent on its own.

DashForm - 为AI代理优化的联系表单和预订表单生成器。
@AIDailyGuy · X
the form built for agents

QuoteFlash是专为手工业者设计的AI报价和发票生成工具,60秒内创建专业文件。
@OyenolaAbdulwa3 · X
Creating invoice for your business made easy 👌

使用 SpecIQ 自动生成符合标准的产品规格表和技术文档。
@speciq_app · X
is a documentation engine that transforms unstructured product details into professional, compliant technical documents. Unlike generic AI chat tools, SpecIQ provides structured templates and branded outputs tailored for real business use.


Argutum:与AI聊天并根据消息质量赚钱。
u/as-333 · Reddit
Built an AI chat that pays you per message, scored in real time: looking for feedback I've been using Claude Code to build Argutum, an AI assistant that scores every message you send (0–100, five dimensions: complexity, novelty, structure, domain expertise, conversational depth) and pays you for the good ones. The underlying idea is that your prompts get sold as training data to AI labs, so you should get a cut instead of it happening for free. Stack: Next.js 16, Groq/Llama 3.3 70B, custom

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