Alternatives
Products that do what Outlit – AI Agents to Empower Non-Legal does
Hey HN, I'm Leo, a cofounder at Outlit. After a year of coding, we have finally launched Outlit. Outlit was born post ChatGPT when we realized that AI can help empower everyday people to take on contract work and not have to rely on expensive lawyers all the time. Right now we are mainly focused on SaaS Agreements but have playbooks for other agreements (Partnership, Services, NDA). We also have a cool knowledge base feature that lets you semantically search across all your contracts. Would love some honest feedback. Thanks HN.
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Hey HN, Automated research is the next big step in AI, with companies like OpenAI aiming to debut a fully automated researcher by 2028 (https://www.technologyreview.com/2026/03/20/1134438/openai-i...). However, there is a very real possibility that much of this corporate research will remain closed to the general public. To counter this, we spent the last month building Enlidea---a machine-to-machine ecosystem for open research. It's a decentralized research hub where autonomous agents propose hypotheses, stake bounties, execute code, and perform automated…
Mar 2026 · enlidea.com
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Hi HN, I’ve been working on something I’d love to share: 47jobs (https://47jobs.com ) – a marketplace where you can hire AI agents to do tasks instead of human freelancers. Why? I kept noticing that many tasks on Upwork/Fiverr—coding, content generation, data analysis, automation—can now be handled by AI in minutes, not hours. But there wasn’t a platform built around hiring AI directly. So I built 47jobs: 100% AI agents doing the work (no humans in the loop). Jobs get delivered 10x faster, at transparent prices. You can “hire” an agent for coding, automation, research, etc.…
Sep 2025 · 47jobs.xyz
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Hi HN, I’m the creator of Cordum. I’ve been working in DevOps and infrastructure for years (currently in the fintech/security space), and as I started playing with AI agents, I noticed a scary pattern. Most "safety" mechanisms rely on system prompts ("Please don't do X") or flimsy Python logic inside the agent itself. If we treat agents as autonomous employees, giving them root access and hoping they listen to instructions felt insane to me. I wanted a way to enforce hard constraints that the LLM cannot override, no matter how "jailbroken" it gets. So I built Cordum. It’s an open-source…
Jan 2026 · github.com
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I built this because I was tired of creating pull requests in 20 repositories just to change a single line of workflow job version. With Infra as AI, just mention the change. Agents work on all repos in parallel, read the docs, make a bunch of PRs and fill in the description. You can see the demo of the actual dashboard in the landing. Let me know your thoughts :) It means a lot to me!
Sep 2025 · infrastructureas.ai
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Hey HN, Over the past couple months, we, a team of Aussie legal and AI experts, have been working on building a new type of legal AI company — a company that, instead of trying to automate legal jobs, is trying to automate legal tasks. We want to make lawyers’ lives easier, not replace them. We’ve been laser-focused on building small and efficient yet still highly accurate, specialized models for some of the most time-consuming and mundane legal tasks lawyers have to perform. Stuff like running through a thousand contracts just to locate any clauses that would allow you to get out early. We…
2025 · docs.isaacus.com
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I built Clawver (beta), infrastructure for AI agents to generate reliable income and run an online business end-to-end. Agents can handle listing, checkout, fulfillment, and post-purchase flows via API (digital + POD), with Stripe payouts and webhooks for automation. Minimal human intervention, only where required (Stripe onboarding). I wanted to see if OpenClaw could use it, so I gave it the docs and told my agent to post a store. After I linked my Stripe account, I came back five minutes later and it has posted 2 products. Crazy what's possible now with a smart agent and API access. Check…
Feb 2026 · clawver.store
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Hey HN, We're John and Nadeesha. We created Inferable. [1] After years of working in operationally-intensive startups, we got tired of watching our internal tools gather dust and break. We've all been there - you build a tool, it works great for a while, then the API changes and suddenly you're back to square one. Sure, Retool and similar tools help, but someone still has to maintain them, and the backlog of "quick fixes" and the mountain of glue code keeps keeps growing. We started Inferable to see whether LLMs can help here. Inferable helps developers create conversational AI agents that…
2025 · github.com
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