Hujing Wenyu Launches Jingrui AI Film Production Platform, Cutting AI Video Costs by Over 30% per Minute

On November 4, Chinese entertainment group Hujing Wenyu (虎鲸文娱) officially launched Jingrui AI, a platform it describes as the industry's first AI-driven film and television production and management system. The launch positions the tool as infrastructure for the whole production cycle rather than a standalone generative-video product.

The concrete number in the announcement, reported by Chinese tech outlet QbitAI, is cost: the platform cuts the per-minute cost of AI video production by more than 30%. That is the clearest verifiable claim attached to the launch, and it frames the product as a margin play for a famously expensive industry.

The pairing of production and management in the platform's positioning points at two needs usually served by separate tools. Production covers generating and processing footage; management covers coordinating projects, assets and workflows. Putting both in one system is what allows AI to enter a crew's daily routine instead of remaining an experiment run by one curious editor.

Film and television has had an ambivalent relationship with generative AI. Studios want cheaper iteration and faster turnaround, but they also worry about quality, rights and controllability. A platform built by an entertainment group itself has an advantage here: model choice, asset provenance and output standards can be tuned to how productions actually work.

If the 30% figure holds up in real projects, the implication goes beyond one company's balance sheet. Content is a high-cost, long-cycle business, and a lower per-minute cost changes which projects are worth greenlighting — especially short-form drama, advertising and marketing assets, where volume is high and per-unit budgets are small.

Three things are worth watching next: whether Hujing Wenyu names actual productions built on the platform, how the cost saving is calculated, and whether Jingrui AI opens to content teams outside the group. Those answers decide whether this is an internal efficiency tool or an industry-facing piece of infrastructure.