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Learn how Nimble's self-learning web search, crawling, and research agents discover deep web data for OpenAI models 👇

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Nimble

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144,821 görüntüleme • 7 gün önce •via X (Twitter)

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Nimble is now an OpenAI plugin for ChatGPT and Codex, giving OpenAI models deeper context from the web. With Nimble, ChatGPT and Codex can: - Discover more complete web context by combining web search with computer use to navigate and paginate websites, capturing data that doesn’t show up in search results - Improve web search efficiency with self-learning agents that optimize web retrieval methodology after every run - Govern web retrieval with source controls, confidence scores, and evidence for every data point Available now in the Plugins tab. Learn more here:
0:39

Nimble is now an OpenAI plugin for ChatGPT and Codex, giving OpenAI models deeper context from the web. With Nimble, ChatGPT and Codex can: - Discover more complete web context by combining web search with computer use to navigate and paginate websites, capturing data that doesn’t show up in search results - Improve web search efficiency with self-learning agents that optimize web retrieval methodology after every run - Govern web retrieval with source controls, confidence scores, and evidence for every data point Available now in the Plugins tab. Learn more here:

Nimble

99,735 görüntüleme • 19 gün önce

Introducing Web Search Agents: expert level web search that self-learns your domain to deliver perfect web context, while burning less tokens. Generic web search tools start from scratch every time they run. Web Search Agents compound their expertise to adapt web search and crawling to your use case — finding the exact data you need, more efficiently. Learn more below in our blog:
1:28

Introducing Web Search Agents: expert level web search that self-learns your domain to deliver perfect web context, while burning less tokens. Generic web search tools start from scratch every time they run. Web Search Agents compound their expertise to adapt web search and crawling to your use case — finding the exact data you need, more efficiently. Learn more below in our blog:

Nimble

363,652 görüntüleme • 2 ay önce

Agents 🤝 Web Search ASI:One now lets you toggle both Agents and Web Search together. Get answers with memory, logic, and real-time data in one go. → Watch how it works 👇
0:58

Agents 🤝 Web Search ASI:One now lets you toggle both Agents and Web Search together. Get answers with memory, logic, and real-time data in one go. → Watch how it works 👇

Fetch.ai

15,829 görüntüleme • 1 yıl önce

Meet Embodied Web Agents that bridge physical-digital realms. Imagine embodied agents that can search for online recipes, shop for ingredients and cook for you. Embodied web agents search internet information for implementing real-world embodied tasks. All data, codes and web environments are available at Paper link:
5:09

Meet Embodied Web Agents that bridge physical-digital realms. Imagine embodied agents that can search for online recipes, shop for ingredients and cook for you. Embodied web agents search internet information for implementing real-world embodied tasks. All data, codes and web environments are available at Paper link:

Yining Hong

55,062 görüntüleme • 1 yıl önce

I built a Deep Research AI Agent team using OpenAI Agents SDK and Firecrawl. It combines multiple AI agents that can autonomously search the web, extract content, and generate detailed reports with enhanced analysis. 100% Opensource Code with step-by-step tutorials.
1:29

I built a Deep Research AI Agent team using OpenAI Agents SDK and Firecrawl. It combines multiple AI agents that can autonomously search the web, extract content, and generate detailed reports with enhanced analysis. 100% Opensource Code with step-by-step tutorials.

Shubham Saboo

50,831 görüntüleme • 1 yıl önce

Introducing web-agent, an open framework for building web agents 🔥 Build AI agents that search, scrape, and interact with the web - powered by the same architecture behind our /agent endpoint. 100% open source. Bring any model. Anthropic, OpenAI, or your own.
0:25

Introducing web-agent, an open framework for building web agents 🔥 Build AI agents that search, scrape, and interact with the web - powered by the same architecture behind our /agent endpoint. 100% open source. Bring any model. Anthropic, OpenAI, or your own.

Firecrawl

123,983 görüntüleme • 5 ay önce

figuring out how to upgrade go version using gpt-oss:120b, ollama's web search MCP server, and OpenAI codex open source models for coding are here
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figuring out how to upgrade go version using gpt-oss:120b, ollama's web search MCP server, and OpenAI codex open source models for coding are here

parth

37,958 görüntüleme • 1 yıl önce

You built an agent and you're still doing research by hand? Give it web search made for agents — CLI, REST, MCP.
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You built an agent and you're still doing research by hand? Give it web search made for agents — CLI, REST, MCP.

Keenable AI

55,809 görüntüleme • 2 ay önce

We're having a blast at Databricks Data + AI Summit! We're talking with builders about three easy ways to bring Nimble's live web search into Databricks: 1. Ask Genie to search the web and bring any data into any table 2. Call Nimble via SQL to enrich your tables 3. Build an end-to-end app on Databricks to monitor and visualize anything on the web
0:40

We're having a blast at Databricks Data + AI Summit! We're talking with builders about three easy ways to bring Nimble's live web search into Databricks: 1. Ask Genie to search the web and bring any data into any table 2. Call Nimble via SQL to enrich your tables 3. Build an end-to-end app on Databricks to monitor and visualize anything on the web

Nimble

62,226 görüntüleme • 3 ay önce

You can now officially use Exa web search inside Grok Build! Exa is the fastest and most accurate web search, built for agents.
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You can now officially use Exa web search inside Grok Build! Exa is the fastest and most accurate web search, built for agents.

Exa

474,477 görüntüleme • 2 ay önce

Bytedance, opensourced DeerFlow (Deep Exploration and Efficient Research Flow) LLM + Langchain + tools (web search, crawler, code exec). Its a community-driven Deep Research framework.
1:27

Bytedance, opensourced DeerFlow (Deep Exploration and Efficient Research Flow) LLM + Langchain + tools (web search, crawler, code exec). Its a community-driven Deep Research framework.

Rohan Paul

104,614 görüntüleme • 1 yıl önce

Introducing the new Firecrawl CLI 🔥 The toolkit for agents to scrape, search, and browse the web. - Scrape clean data from any page - Search the web and get full results back - Spin up cloud browsers for interactive flows npx -y firecrawl-cli@latest init --all --browser
0:43

Introducing the new Firecrawl CLI 🔥 The toolkit for agents to scrape, search, and browse the web. - Scrape clean data from any page - Search the web and get full results back - Spin up cloud browsers for interactive flows npx -y firecrawl-cli@latest init --all --browser

Firecrawl

357,170 görüntüleme • 7 ay önce

🚨 THIS IS ACTUALLY INSANE Your AI agent can have access to the web. But if it can't reliably read what’s actually on the page, that access is almost useless. We looked at Firecrawl as the web layer for AI agents and the numbers are hard to ignore. The setup is simple: Give it a URL, search query, or website. Firecrawl handles the ugly part — crawling, scraping, rendering, extracting, and turning web content into something an AI model can actually use. The headline numbers: → 173,000+ GitHub stars → Search, scrape and interact with the web at scale → Supports web pages, PDFs, DOCX and other content → Structured data extraction for AI workflows → MCP support for connecting it directly to AI agents The workflow looks like this: Search → Scrape → Crawl → Extract → Feed the agent Three things stand out: 1. Scraping becomes an infrastructure layer Instead of maintaining your own pile of HTTP clients, parsers, browser automation and retry logic, you can treat web access as an API. 2. Agents get more than raw HTML The goal isn't just downloading a webpage. It's turning messy web content into clean context that an LLM can reason over. 3. The same layer works across different agent workflows Research agents. RAG pipelines. AI search. Competitive intelligence. Web-data extraction. The interesting shift: AI agents don't just need better models. They need better access to the information those models are supposed to reason about. Firecrawl is building that layer. Save this repo.
0:28

🚨 THIS IS ACTUALLY INSANE Your AI agent can have access to the web. But if it can't reliably read what’s actually on the page, that access is almost useless. We looked at Firecrawl as the web layer for AI agents and the numbers are hard to ignore. The setup is simple: Give it a URL, search query, or website. Firecrawl handles the ugly part — crawling, scraping, rendering, extracting, and turning web content into something an AI model can actually use. The headline numbers: → 173,000+ GitHub stars → Search, scrape and interact with the web at scale → Supports web pages, PDFs, DOCX and other content → Structured data extraction for AI workflows → MCP support for connecting it directly to AI agents The workflow looks like this: Search → Scrape → Crawl → Extract → Feed the agent Three things stand out: 1. Scraping becomes an infrastructure layer Instead of maintaining your own pile of HTTP clients, parsers, browser automation and retry logic, you can treat web access as an API. 2. Agents get more than raw HTML The goal isn't just downloading a webpage. It's turning messy web content into clean context that an LLM can reason over. 3. The same layer works across different agent workflows Research agents. RAG pipelines. AI search. Competitive intelligence. Web-data extraction. The interesting shift: AI agents don't just need better models. They need better access to the information those models are supposed to reason about. Firecrawl is building that layer. Save this repo.

Vikas gupta

20,117 görüntüleme • 1 ay önce

Introducing /search - the simplest way for agents and devs to discover the web 👀 Our #1 most requested endpoint is finally here. Search the web AND scrape all results in an LLM-ready format with one API call. Now live on our API, MCP, and all integrations 🔥
1:34

Introducing /search - the simplest way for agents and devs to discover the web 👀 Our #1 most requested endpoint is finally here. Search the web AND scrape all results in an LLM-ready format with one API call. Now live on our API, MCP, and all integrations 🔥

Firecrawl

390,902 görüntüleme • 1 yıl önce

Introducing OpenAI o3 and o4-mini—our smartest and most capable models to date. For the first time, our reasoning models can agentically use and combine every tool within ChatGPT, including web search, Python, image analysis, file interpretation, and image generation.
0:44

Introducing OpenAI o3 and o4-mini—our smartest and most capable models to date. For the first time, our reasoning models can agentically use and combine every tool within ChatGPT, including web search, Python, image analysis, file interpretation, and image generation.

OpenAI

3,724,371 görüntüleme • 1 yıl önce

Parallel is now integrated with Zapier Use this integration to give any automation access to powerful structured web search, for example: - Slack bots that enrich leads - Inbound emails to trigger deep research reports - Market research agents Here's Kumar Saunack for a demo:
3:02

Parallel is now integrated with Zapier Use this integration to give any automation access to powerful structured web search, for example: - Slack bots that enrich leads - Inbound emails to trigger deep research reports - Market research agents Here's Kumar Saunack for a demo:

Parallel Web Systems

39,671 görüntüleme • 10 ay önce

This is a wild use case! I used Gamma + n8n to automatically generate a complete presentation on AI Agents research. In just minutes! It combines web search (for research), GPT-5 (narrative), and Gamma (for slide content generation). Full workflow breakdown below 👇
0:35

This is a wild use case! I used Gamma + n8n to automatically generate a complete presentation on AI Agents research. In just minutes! It combines web search (for research), GPT-5 (narrative), and Gamma (for slide content generation). Full workflow breakdown below 👇

elvis

50,758 görüntüleme • 11 ay önce