金融商业1 week ago
Lightworks — The QMS for Quality Managers shipping AI
AI 医疗设备初创公司的质量管理系统。
@ZachInSpace · X
Launched a month ago
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15 projects
AI 医疗设备初创公司的质量管理系统。
@ZachInSpace · X
Launched a month ago
PortWise AI投资顾问，提供市场分析和投资组合解读。
PortWise — AI 投资顾问，将市场数据、公司公告、新闻资讯和交易信号转化为关于股票、ETF 和投资组合的通俗易懂的回答
Analyzes why your emails land in spam and provides AI-powered fixes to improve inbox placement.
ismaelyws · HN
Hey HN, I built an email deliverability SaaS with a RAG system. It's trained on all my knowledge and hundreds of real deliverability use cases from 4+ years experience as an Email Deliverability Specialist on Upwork. It solves a frustration problem a lot of businesses are experiencing. I'm looking for feedback so let me know in the comments.
用12个自主AI代理自动化邮件、支持和内容创建。
@BainPath · X
Discover - Your AI Workforce. Let’s connect !
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
Cricket AI：输入网址获得网站审计、30天营销策略和每日内容文案。
@ahntany · X
Good to see you:) I'm working on ai marketing tool :
AI交易日志，导入交易并追踪睡眠和压力来发现成功的驱动因素。
@QuantBuddyAI · X
And just getting started!!
seus.ai 自动设计、构建和部署软件系统。
@Bim_evaporates · X
Check out DMs open
用一行代码部署强大的 AI 模型，享受业界最具竞争力的 GPU 价格。
Synexa AI — 一行代码部署 AI 模型 (Replicate 50% 低价平替)，Synexa 是运行无服务器 AI API 最具性价比的解决方案，提供业界最具竞争力的 A100 GPU 价格，相比其他服务商可节省高达 62% 的 AI 算力成本 - [更多介绍](https://github.com/1c7/chinese-independent-developer/issues/47
AI工具在90秒内通过财务分析和风险评估来压力测试商业创意。
@AIWMCX1 · X
Consultants don’t need more noise. AIWMC Quantis helps turn messy business ideas into clear scenarios, runway views, and risk signals — so you can spend less time rebuilding analysis and more time giving the client a real answer.
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.
用于构建网站、编写代码和处理复杂任务的 Agentic AI 助手。
@durdom_evm · X
Chinese team at just dropped ZCode 3.0 and it's quietly reshaping the agentic coding landscape while everyone's waiting on Anthropic's roadmap here's what matters: GLM-5.2 is trading blows with Opus 4.8 on the benchmarks that actually count. 81.0 vs 85.0