Index
Parallel Web Systems launched Index, a platform to help content owners understand how AI agents use their work and earn revenue based on its "Shapley value."
Deep dive
- Index, by Parallel Web Systems, provides a mechanism for content owners to monitor and monetize the use of their work by AI agents.
- Compensation is determined by estimating the "Shapley value" of content, which measures its unique marginal contribution to an agent's output.
- This model aims to create an incentive-aligned economic system for the "agentic web," where AI agents are expected to use content far more extensively than humans.
- Initial partners include major publications like The Atlantic and Fortune Magazine, as well as data providers and individual creators such as Alex Heath and Packy McCormick.
- The platform leverages Parallel Web Systems' existing web index and retrieval infrastructure, which also powers their Extract API for fetching content from complex web pages.
- This initiative directly responds to the legal and ethical debates surrounding AI training data and intellectual property rights.
Decoder
- Shapley value: A concept from cooperative game theory used here to quantify the marginal contribution of a specific piece of content to an AI agent's output, helping determine its value for compensation.
- Agentic web: A term referring to a future iteration of the internet where AI agents, rather than primarily human users, are the primary consumers and interactors with web content.
Original article
Today we're launching Index: a platform for content owners to understand how AI agents use their work, and earn revenue when they do.
Our first partners include @TheAtlantic, @FortuneMagazine, @PRNewswire, @PitchBook, @ZoomInfo, @Tracxn, @RocketReachCo, @enigma_data, @fiscal_ai, plus creators @alexeheath, @mariogabriele @azeem, @every, and @packyM.
Compensation in Index is calculated by estimating each source's Shapley value: its marginal contribution to an agent's answer at the moment of inference.
Content that's uniquely valuable, hard to replace, or used in high-value agent work earns more.
AI agents are the web's second user. They'll use it 1000x more than humans ever have.
The economic model of the web was built for human users. Index is a new, incentive-aligned model for the agentic web.
See how agents are using your content at index.parallel.ai
Today, we're launching Parallel Extract, a new API in our Agent Tools bundle.
When given a URL, Extract fetches all content from that page and returns it in markdown, either in full detail or in a compressed form for better token efficiency.
Extract is built on the same proprietary web index and retrieval infrastructure that powers our Search, Task, FindAll, and Monitor APIs.
This means reliable extraction from the most challenging sites— JavaScript-heavy pages, multi-page PDFs with images, and dynamic content that only loads client-side.
How customers have been using Extract:
- Pull complete API docs and code examples
- Extract methodology from research papers
- Retrieve specific sections from 10-Ks and financial filings
- Get complete product details from ecom sites
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