Alternatives
Products that do what You know browser-use, here's human-use for LLMs to get info from humans does
We made human-use. Similar to how browser-use connects agents to the web, human-use connects agents to people all over the world in real-time using the Rapidata API. This allows the LLM to crowdsource human feedback and insights when it deems necessary. Free to use for anyone, you can enable your agent to use humans in real-time to: - Do preference research - Check for hallucinations - Capture sentiment - Get feedback - etc. Whatever you would want from humans. We expose certain parts of the Rapidata API to the agent through the MCP server framework. Additionally we provide a custom client.…
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Hey HN, I made Browser-Use, an open-source tool that lets (all Langchain supported) LLMs execute tasks directly in the browser just with function calling. It allows you to build agents that interact with web elements using natural language prompts. We created a layer that simplifies website interaction for LLMs by extracting xPaths and interactive elements like buttons and input fields (and other fancy things). This enables you to design custom web automation and scraping functions without manual inspection through DevTools. Hasn't this been done a lot of times? Good question, as a general…
2024 · github.com
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I spent a few hours last weekend testing whether AI can replace code by executing directly. Built a contact manager where every HTTP request goes to an LLM with three tools: database (SQLite), webResponse (HTML/JSON/JS), and updateMemory (feedback). No routes, no controllers, no business logic. The AI designs schemas on first request, generates UIs from paths alone, and evolves based on natural language feedback. It works—forms submit, data persists, APIs return JSON—but it's catastrophically slow (30-60s per request), absurdly expensive ($0.05/request), and has zero UI…
Nov 2025 · github.com
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Hey HN, I'm excited to share BrowserBee, a privacy-first AI assistant in your browser that allows you to run and automate tasks using your LLM of choice (currently supports Anthropic, OpenAI, Gemini, and Ollama). Short demo here: https://github.com/user-attachments/assets/209c7042-6d54-4fc... Inspired by projects like Browser Use and Playwright MCP, its main advantage is the browser extension form factor which makes it more convenient for day to day use, especially for less technical users. Its also a bit less cumbersome to use on websites that require you to be…
2025 · github.com
- 5WU
Hey HN – Gregor & Magnus here again. A few months ago, we launched Browser Use (https://news.ycombinator.com/item?id=43173378), which let LLMs perform tasks in the browser using natural language prompts. It was great for one-off tasks like booking flights or finding products—but we soon realized enterprises have somewhat different needs: They typically have one workflow with dynamic variables (e.g., filling out a form and downloading a PDF) that they want to reliably run a million times without breaking. Pure LLM agents were slow, expensive, and unpredictable for these…
2025 · github.com
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2023 · tinyllms.vercel.app
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Hey HN, Hakim here from Fini (YC S22), a startup focused on providing automated customer support bots for enterprises that have a high volume of support requests. Today, one of the largest use cases of LLMs is for the purpose of automating support. As the space has evolved over the past year, there has subsequently been a need for evaluations of LLM outputs - and a sea of LLM Evals packages have been released. "LLM evals" refer to the evaluation of large language models, assessing how well these AI systems understand and generate human-like text. These packages have recently relied on…
2024 · github.com
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Agents using isolated computers to get work done like humans
Sep 2025
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Browser LLM demo working on JavaScript and WebGPU. WebGPU is already supported in Chrome, Safari, Firefox, iOS (v26) and Android. Demo, similar to ChatGPT https://andreinwald.github.io/browser-llm/ Code https://github.com/andreinwald/browser-llm - No need to use your OPENAI_API_KEY - its local model that runs on your device - No network requests to any API - No need to install any program - No need to download files on your device (model is cached in browser) - Site will ask before downloading large files (llm model) to browser cache - Hosted on Github…
2025 · andreinwald.github.io
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I found myself building a bunch of LLM-backed features that needed to use tool calling, and some of those tools involved doing things that were somewhat high stakes - communicating on my behalf or modifying shared / production data. one example - I wanted to replace a marketing website with a chatbot + vector DB loaded with the previous content, docs, and blog posts. Between hallucinations, missing knowledge base info, and the LLM generally writing like an psuedo-intellectual high schooler, I realized I couldn't trust it to communicate unsupervised with my website visitors. I needed a…
2024 · github.com
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Check out this impressive project that enables running LLMs entirely in the browser using WebGPU. Key features: - Zero token costs, no cloud infrastructure required - Complete data privacy through local processing - Simple 3-line code integration - Built on MLC and Transformer.js The benchmarks show smaller models can effectively handle many common tasks. Currently the project roadmap includes: - No-code AI pipeline builder - Browser-based RAG for document chat - Analytics/logging - Model fine-tuning interface
2025 · github.com
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Hi, I've been watching the rise of AI agents with a mix of excitement and dread. We're building incredible tools that can browse the web, but we're forcing them to navigate a world built for human eyes. They scrape screens and parse fragile DOMs. We're trying to tame them to act like humans. I believe this is fundamentally wrong. The goal isn't to make AI operate at a human level, but to unlock its super-human potential. The current path is dangerous. When agents from OpenAI, Google, and others start browsing at scale and speed, concepts like UI/UX will lose meaning for them. The entire…
2025 · github.com
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Hey HN, I built browser-use, an open-source alternative to OpenAI’s Operator for browser-use systems, and here’s why I think it’s better: Flexibility: You can use any LLM with our tool – Gemini, Anthropic, Qwen, Llama, DeepSeek, and more. As new models improve, so does your agent. Open Source: No need to pay $200/month or endure long waitlists – it’s free and accessible to everyone today. Custom Automation: Our Python package allows you to build actual web automations. Your LLM can gain new tools, like file uploads. Cost: Our system is 30x cheaper than Operator, e.g., when used with…
2025 · github.com
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Hi HN! Run it: OPENROUTER_API_KEY="sk" npx bff-eval --demo We built a tool to help people take LLM outputs and easily grade them / eval them to know how good an assistant response is. We've built a number of LLM apps, and while we could ship decent tech demos, we were disappointed with how they'd perform over time. We worked with a few companies who had the same problem, and found out scientifically building prompts and evals is far from a solved problem... writing these things feels more like directing a play than coding. Inspired by Anthropic's constitutional ai concepts, and amazing…
2025 · github.com
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Looking for feedback on how Props can make your life easier as an LLM application developer.
2024 · wwww.getprops.ai
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We’re building an open-source tool that makes it easy to expose secure, LLM-optimized APIs on top of your structured data—without manually designing endpoints or worrying about compliance. AI agents and LLM-powered applications need structured access to data, but traditional APIs and databases weren’t built with AI workloads in mind. Our tool automatically generates APIs that: - Filter out PII & sensitive data to comply with GDPR, CPRA, SOC 2, and other regulations. - Provide traceability & auditing, so AI apps aren’t black boxes, and security teams stay in control. - Optimize for AI…
2025 · github.com
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I feel like LLMs can help me understand anything. However, after I get a summary, I can't dive in to parts that I find interesting; can't refer to original source easily and can't control context with chatbots. This is an attempt to solve for a complete knowledge consumption experience with AI . Please give me feedback!
Oct 2025 · kerns.ai
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