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Chinese AI startup Manus, which made headlines earlier this year for its approach to a multi-agent orchestration platform for consumers and “pro”-sumers (professionals wanting to run work operations), is back with an interesting new use of its technology.
While many other major rival AI providers such as OpenAI, Google, and xAI that have launched “Deep Research” or “Deep Researcher” AI agents that conduct minutes or hours of extensive, in-depth web research and write well-cited, thorough reports on behalf of users, Manus is taking a different approach.
The company just announced “Wide Research,” a new experimental feature that enables users to execute large-scale, high-volume tasks by leveraging the power of parallelized AI agents — even more than 100 at a single time, all focused on completing a single task (or series of sub-tasks laddering up said overarching goal).
Manus was previously reported to be using Anthropic Claude and Alibaba Qwen models to power its platform.
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Parallel processing for research, summarization and creative output
In a video posted on the official X account, Manus co-founder and Chief Scientist Yichao ‘Peak’ Ji shows a demo of using Wide Research to compare 100 sneakers.
To complete the task, Manus Wide Research nearly instantly spins up 100 concurrent subagents — each assigned to analyze one shoe’s design, pricing, and availability.
The result is a sortable matrix delivered in both spreadsheet and webpage formats within minutes.
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