SocialFetch.dev
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Labeling AI
Social Fetch is the social media data API for teams that need to ship features, not maintain scrapers.
Every major platform changes its DOM, blocks proxies, and breaks homegrown integrations. Social Fetch handles that infrastructure โ headless browsers, rate limits, normalization โ so you get clean, live JSON back on every request. No stale cache. No per-platform parsers in your codebase.
What you can fetch: profiles and follower data, posts and reels, comments and threads, video transcripts, hashtag/keyword search, ad library intelligence, and engagement metrics โ across TikTok, Instagram, YouTube, X, LinkedIn, Facebook, Reddit, Threads, GitHub, Spotify, and more.
Built for: creator tools, marketing analytics, brand safety and impersonation detection, competitive intelligence, enrichment pipelines, monitoring dashboards, and AI agent workflows. Integrate with cURL, Python, Node, our official TypeScript SDK, or our MCP server for Cursor and Claude.
Pricing: pay-as-you-go credits that never expire. No monthly subscription. Start with 100 free credits โ no credit card required.
A complete solution for your training data problem with fast labeling tools, human workforce, data management, a powerful API and automation features.
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SocialFetch.dev's answer
Social Fetch provides a unified REST API that lets developers collect public data from 20+ social platforms โ TikTok, Instagram, YouTube, X, LinkedIn, Reddit, Facebook, Threads, and more โ using a single consistent JSON schema. There is no need to learn or maintain separate APIs for each network. Credits never expire, and you only pay for what you use, making it ideal for both prototyping and production-scale data pipelines.
SocialFetch.dev's answer
Unlike solutions that require you to set up and maintain separate API integrations for each platform, Social Fetch gives you one API key and one consistent schema across all supported networks. You get the same response structure whether you are fetching TikTok videos, Instagram posts, or YouTube channels. The pay-as-you-go model means no wasted monthly spend on idle subscriptions, and credits never expire so there is no pressure to use them up.
SocialFetch.dev's answer
Social Fetch is primarily used by developers, data engineers, and growth marketers who need programmatic access to social media data without building and maintaining individual platform integrations. Common use cases include social analytics tools, influencer research platforms, content aggregation pipelines, brand monitoring dashboards, and AI training datasets that require large-scale social content.
SocialFetch.dev's answer
Social Fetch was founded by Luke Askew, a developer who repeatedly ran into the same problem while building social analytics tools: every platform had a different API, different authentication flows, different rate limits, and different response shapes. Building and maintaining integrations for even a handful of platforms was a significant ongoing burden. Social Fetch was created to solve this by acting as a single abstraction layer, so developers can focus on what they are building rather than on the plumbing beneath it.
SocialFetch.dev's answer
Social Fetch is built on Next.js and TypeScript, deployed on Vercel. The API layer is serverless and runs on edge infrastructure for low latency globally. Data is processed and stored using cloud-native services, and the platform uses tRPC for type-safe internal APIs. The codebase is a TypeScript monorepo, enabling shared types between the API, frontend, and internal tooling.
SocialFetch.dev's answer
Social Fetch is currently used by early-stage startups, independent developers, and small analytics teams. As a newer product launched in 2024, we are still growing our customer base. If you are interested in using Social Fetch or would like to be featured here, please reach out at hello@socialfetch.dev.
Service goes down often. Very slow team. Slow support.
Based on our record, Labelbox seems to be more popular. It has been mentiond 10 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Cursor's security agents primarily operate in the first dimension, catching vulnerabilities in code. That's valuable and necessary work. But as you'll see in the walkthrough below, the other two dimensions matter just as much, especially at enterprise scale. And the organizations getting the best results, like Labelbox, which cleared a multi-year vulnerability backlog by running Cursor and Snyk together, are the... - Source: dev.to / 5 months ago
Use tools like Weights & Biases, Labelbox, or Maximโs data engine to version your datasets, track changes, and continuously add new edge cases and user feedback. - Source: dev.to / about 1 year ago
Labelbox | Remote | Frontend / WebGL, Backend, Engineering Managers | https://labelbox.com Labelbox is building the training data platform to power breakthroughs in machine learning. We provide an end to end solutions for the full AI lifecycle from creating catalogs of unstructured data all the way to building the tools for humans to label the data to teach machines. Why choose us? - Source: Hacker News / almost 4 years ago
Hey, I have currently developed a U-Net model for segmentation and I am trying to use the model assisted labeling feature on LabelBox to annotate some masks, so I can save time on relabeling. I am just wondering if anyone is familiar with this feature or can give me a step by step guideline on how to go about doing this. I went through the examples on their GitHub but Iโm honestly still very confused. Any help... Source: about 4 years ago
By now, I hope you see where I'm going with this. What is MDR doing? They're creating the labelled data used to train severance chips. They get a raw download of human brains in encoded format, and go about manually labelling the different pieces based on their most basic elements. Then, based on this manually labelled data, an algorithm can be trained to create a severance chip. MDR is basically Labelbox for... Source: about 4 years ago
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