Startup Parallel Web Systems Inc. launched a cloud platform today designed for conducting online research in AI applications.

The two-year-old company is led by former Twitter CEO Parag Agrawal and has secured $30 million in funding from investors including Khosla Ventures, First Round Capital, and Index Ventures. A detailed blog post published today outlines the platform's features.

Parallel's solution enables AI models to integrate public web data into prompt responses. The company claims its software processes millions of research tasks daily for early adopters - including "some of the fastest-growing AI companies" - as disclosed in the blog post.

The platform offers eight distinct AI research engines with varying capabilities. The most cost-effective engine delivers results within one minute, while the top-tier Ultra8x engine requires up to 30 minutes to complete complex research tasks that retrieve detailed information.

All prompt responses include confidence scores to assess data quality, along with citations for easier verification. Users can customize how collected information is organized, such as formatting competitor product reviews into three-column spreadsheets or adjusting computational resources allocated to each task.

Benchmark tests using BrowseComp and DeepResearch Bench showed Parallel's Ultra8x engine outperforming GPT-5 by over 10% in both metrics. The company provides three APIs for platform access: a general task API, a search API optimized for AI agents, and a low-latency API for chatbots and real-time applications.

In the blog post, Parallel announced plans to expand its platform's use cases and develop AI agents capable of completing "team-sized tasks within hours." Future updates will enable autonomous operation execution when web content changes.