Startup Parallel Web Systems Inc. today launched a cloud platform that artificial intelligence applications can use to conduct online research.
The two-year-old company is led by former CEO of Twitter Inc. Parag Agrawal. Parallel is supported by Khosla Ventures, First Round Capital, Index Ventures and other investors. The information reported last January that the company raised $30 million in funding.
Parallel's platform allows AI models to incorporate data from the public web into rapid responses. According to the company, the software already completes millions of research tasks per day for early adopters. These customers include “some of the fastest growing AI companies.” Blog post Released today.
The company says its platform will be useful for a wide range of use cases. For example, AI programming assistants can leverage software to pull code from a GitHub repository. Retailers can use it to gather information about rival product catalogs.
The platform provides access to eight AI research engines with a variety of features. The fastest and most cost-effective engine can process requests in less than a minute. Parallel's most capable engine, Ultra8X, takes up to 30 minutes to get more detailed information and complete one research task.
The platform's rapid response includes a trust score that helps customers assess the quality of the data they have obtained. Additionally, Parallel provides citations that make data validation easier.
Customers can optionally organize information they collect in a specific format on the platform. For example, companies can organize product reviews from competitors' websites in parallel with three column spreadsheets. You can also customize other details, such as the amount of computing capacity the platform uses to complete each research task.
Parallel compared its platform to the GPT-5 ahead of its launch today. In this evaluation, we used BrowseComp and Deepresearch Bench. This is two benchmarks that test the ability to conduct online surveys for LLMS. Parallel's top-end Ultra8X Research Engine outperforms GPT-5 by more than 10% on both benchmarks.
The AI model allows access to the company's platform through three application programming interfaces. There is a generic task API and a search API that is specifically optimized for powering AI agents. Parallel's third API is designed for chatbots and other applications that prioritize low latency.
In today's launch blog post, the company showed its work to expand the scope of use cases the platform supports. The company wants to facilitate the creation of AI agents that “complete the entire team's work in just a few hours.” Additionally, we plan to provide agents with the ability to automatically perform actions in response to changes in the web page.
image: parallel
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