
SignedIn5 — Proposals that close themselves
创建和发送能在数分钟内签署的专业提案。
@ApexEarn · X
Hey, I am Building SignedIn5 A proposal platform for freelancers to create, send, track, and get proposals signed in minutes. Right Now, I am Looking for feedback !!
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创建和发送能在数分钟内签署的专业提案。
@ApexEarn · X
Hey, I am Building SignedIn5 A proposal platform for freelancers to create, send, track, and get proposals signed in minutes. Right Now, I am Looking for feedback !!

ColabWize 审计学术引用并验证作者身份,证明学术工作的真实性。
@clawncore · X

通过稳定化名在私密讨论中获得诚实反馈。
@wheesperapp · X
I built Wheesper to help people speak honestly without losing the context of a real conversation. It evolved from anonymous feedback into private, threaded discussions with stable pseudonyms and moderation controls. Check it out

招聘AI同事,在3D办公室中协作完成任务。
@Anwaritoovvy · X
I’m opening the beta for Remotely. Remotely is an AI operating system for companies — a company brain inside a 3D workspace where teams, tasks, dashboards, communication, and AI agents come together. Try it here: I’m looking for feedback from founders

连接非洲学生和专业人士的职业社交网络平台。
@Zeunetworkapp · X
We’re building ZEUNETWORK, a platform connecting talents to opportunities through jobs, internships, scholarships, networking and business. Connecting talents to opportunities.

支持100多种语言的音频和视频转录,使用AI定制简历,查找远程工作机会。
@OauthNature · X
Ai cv tailoring job board


ServiceInvoice 帮助手工业和贸易企业管理客户、记录工作并发送品牌发票。
@serviceinvoices · X

管理学术会议:提交和审阅论文、处理日程安排和注册。
@harryjwang · X
I've used many of the major conference systems. Plenty still have docs as an unsearchable static site — or worse, as PDFs that stopped tracking the product three versions ago. Somehow, still true in 2026. We took an AI-first path with instead. Our docs are generated from the codebase itself. A custom Claude Code skill writes each page and retakes the screenshots whenever a feature changes — so the docs don't drift from the product. Every page still gets reviewed by a human before it ships. Now you can talk to them, too. We just shipped "Ask AI" over our docs: This feature also turned out to be a nice teaching case for agentic RAG vs. classic RAG: • Classic RAG: chunk → embed → vector DB → retrieve once, by fixed rules • Agentic RAG: hand the model a search tool and let it drive — write a query, read the results, rewrite, retry At more than 100 pages, still no vector database needed. And every answer cites the exact page it came from. #Age


Affynk 统一链接管理交易全流程:预约会议、签署合约、收取付款
@abhinav__dubey · X
Heyy Yooo! Building one link that helps SMBs go from first pitch to fully paid process, no juggling four tools to get there.
