Sima 1.0: A Collaborative Multi-Agent Framework for Documentary Video Production

2026-04-08

AI Summary

This work addresses the challenge of producing high-quality, long-form documentaries on a weekly basis—a task traditionally hindered by lengthy production cycles and intensive human labor. The paper introduces the first systematic multi-agent framework designed for end-to-end documentary production, employing a hybrid human-AI workflow: human creators focus on ideation and filming, while layered AI agents collaboratively handle script annotation, video editing, subtitle refinement, and media asset integration. This approach substantially reduces the creative burden on human producers while maintaining high content quality, thereby establishing the first stable and efficient paradigm for automated weekly production of long-form documentary videos.

Abstract

Content creation for major video-sharing platforms demands significant manual labor, particularly for long-form documentary videos spanning one to two hours. In this work, we introduce Sima 1.0, a multi-agent system designed to optimize the weekly production pipeline for high-quality video generation. The framework partitions the production process into an 11-step pipeline distributed across a hybrid workforce. While foundational creative tasks and physical recording are executed by a human operator, time-intensive editing, caption refinement, and supplementary asset integration are delegated to specialized junior and senior-level AI agents. By systematizing tasks from script annotation to final asset exportation, Sima 1.0 significantly reduces the production workload, empowering a single creator to efficiently sustain a rigorous weekly publishing schedule.

Problem

• documentary video production
• content creation
• manual labor
• video editing
• production pipeline

Innovation

• multi-agent system
• documentary video production
• human-AI collaboration
• automated video editing
• content creation pipeline