oneoneone
SN111A decentralised protocol for accessing user-generated content across the web
A decentralized network that scrapes, validates, and serves user-generated content from platforms like Google Maps and Yelp, enhanced with AI-powered authenticity detection and sentiment analysis.
// Real user content, decentralized and AI-enhanced.
oneoneone is a Bittensor subnet that collects, validates, and serves user-generated content from across the web. Miners scrape reviews, forum posts, and social content from platforms like Google Maps and Yelp, while validators ensure quality through synthetic challenges. The cleaned and enriched data is then sold through a monetized API.
The simple version: Think of it as a decentralized web scraper combined with an AI content analyst. Instead of one company crawling the web (and getting blocked), hundreds of miners do it simultaneously, and AI checks the results for authenticity, sentiment, and intent.
Centralized equivalent: Companies like Apify, Bright Data, and ScrapingBee offer web scraping APIs. oneoneone competes by distributing the work across a decentralized network and adding AI-powered content analysis on top.
How it works:
- Miners collect user-generated content from various platforms using a Node.js-based scraping stack, clean and format the data, and submit it to validators within time constraints.
- Validators issue scraping challenges (both synthetic and organic), assess data quality through spot checks and held-out test data, and score miners on speed (30%), volume (50%), and recency (20%).
- The problem it solves: User-generated content is the raw material for market research, sentiment analysis, AI training, and business intelligence. But collecting it at scale is expensive, fragile (platforms block scrapers), and produces unreliable data.
- The opportunity: The demand for authentic, real-time user data is growing as AI models need training data and businesses need market signals. A decentralized collection network offers redundancy and scale that single-operator scrapers cannot match.
- The Bittensor advantage: Hundreds of independent miners scraping simultaneously creates natural redundancy against platform blocks. The incentive structure rewards speed and volume, while validators ensure quality through both synthetic and organic validation.
- Traction signals: The subnet has 247 active miners, significant participation that suggests the incentive model is working. The API is live at oneoneone.io with subscription-based access, and profits are distributed back to network participants through a buyback mechanism.
Category: Data Scraping and Archival | Centralized Competitor: Apify, Bright Data, ScrapingBee
oneoneone targets a practical and immediately monetizable use case, structured data collection at scale. While many Bittensor subnets focus on cutting-edge AI research, oneoneone addresses the more mundane but commercially valuable problem of getting clean, validated web data into the hands of developers and businesses.
Mechanism:
The network operates on a challenge-response model. Validators generate scraping challenges for specific platforms and content types. Miners race to collect, clean, and structure the data within time constraints. The validation system is dual-layered: synthetic rounds every 30 minutes test miners against known datasets, while organic requests validate real-world performance.
Once collected and validated, the content passes through AI enrichment layers that perform authenticity detection (filtering spam and bot-generated content), intent classification (complaints, praise, questions), emotion and sentiment analysis, and multi-language translation. This enrichment transforms raw scraped data into structured, analyzable content.
The monetization model is straightforward: oneoneone.io sells API access to the enriched data, and profits flow back to network participants. This creates a direct link between subnet utility and miner rewards.
Price has surged 31% over 30 days and 14.6% in the last week, significantly outperforming most subnets. At 0.00518 TAO with a market cap around 17,845 TAO, the momentum suggests growing awareness of the commercial use case.
- Platform resistance: Google, Yelp, and other platforms actively fight scraping. If major platforms implement more aggressive anti-scraping measures, miner output could drop significantly.
- Competition: Well-funded centralized scraping services have years of infrastructure and anti-detection systems built up. oneoneone needs to prove its decentralized model produces equivalent or better results.
- Development visibility: No GitHub contributor or commit data is available in the on-chain snapshots. The 247 active miners suggest the system works, but verifying development health from public data is limited.
Into the next one.