The full gallery
Tech stack
60 projects
Centralize contracts and receive WhatsApp alerts before auto-renewals with AI-powered PDF extraction.
lucas_perego · Product Hunt
Paecto AI contract manager that alerts you before every renewal
Generate, analyze, and negotiate professional contracts using AI.
@Anastasiiakdmk1 · X
Just shipped major updates to ContractAI 🚀 ✅ Professional contracts in 8 languages ✅ AI Credits packs (buy extra generations) ✅ Full plan comparison table ✅ Onboarding tour ✅ Chrome extension Try free: Demo: #buildinpublic #saas #legaltech #ai
Study Tibetan Buddhist texts with AI-powered guidance, daily insights, and note-taking exercises.
@Neymarnad · X
最近一直在做的 Vajra AI 已经上线了。 这是一个 AI-native 的智慧学习平台，希望用 AI 帮助大家更深入地阅读、理解和实践经典智慧。 如果你有空，欢迎体验一下，也很期待听听你的真实反馈。 🔗
Manage your subscriptions privately without linking your bank or email accounts.
@MySubLedger · X
SubLedger is a privacy-first subscription tracker built for the way subscriptions actually work — shared family plans, employer reimbursements, and multiple devices.
Create any contract in 60 seconds and get AI risk analysis before signing.
@Gaurav_dev01 · X
Visual editor for configuring multi-agent LLM systems with local inference.
sascha10000 · HN
Multi-agent LLM editor with local inference via WebSockets
Semantic caching reduces LLM token costs and latency for AI queries.
u/ornymo_official · Reddit
how to reduce ai costs there are lots of way to reduce costs but there all complex to setup i know this cause i tried one in production so i built ornymo we cache meaning not the exact string allowing us to give same awnsers thus reducing llm costs and latency check it out at ornymo.com free for a limited time and let me know your feedback submitted by /u/ornymo_official to r/buildinpublic [link] [comments]
FAIR continuously scans M&A activity in your tech sector and delivers weekly intelligence on potential buyers, market moves and timing — so you can sell on your terms, at a fair pr
@x23labs · X
An LLM agent that tracks goals and plans across sessions while showing exactly what it retrieves, verifies, and fails on.
u/OGMYT · Reddit
I built LOLM, a lower-cost LLM agent that shows what it actually did — looking for blunt feedback I’m one of the founders/builders behind LOLM. Most AI products show an answer but hide whether the system retrieved anything useful, verified the result, switched models, hit a limit, or simply stopped. LOLM exposes those parts through controller events and run receipts. It includes: - Live agent - CLI - Coding and small app-building workflows - Memory and self-hosting options - Control decis
@Joi2James https://t.co/yhieTRvF7k
@iliadubovtsev · X
Dedicated space for team discussions too important for chat and too dynamic for static documentation.
Mike-Kelner · HN
Vostorq – I built the anti-Slack after working at a Slack-first company
Document property conditions neutrally to protect rental deposits and resolve disputes.
@keepthedeposit · X
