Baidu AI Cloud Media and Entertainment China Translated from Chinese

Hanhao Technology (FilmAction.ai)

FilmAction needed reliable cloud infrastructure so its AI filmmaking product could generate scripts, storyboards, images, video, voice and music quickly enough for commercial creative workflows.

Traditional creative cycles that took weeks can be compressed to minute-level delivery.

Reported impact

Business outcome

FilmAction gained a production-grade AI media backbone that keeps creation responsive, reduces business risk from instability and supports a much faster content-creation cycle for users.

  • Customer Experience
  • Scalability
  • Speed to Market

Solution

FilmAction.ai used Baidu AI Cloud to give its one-stop AI filmmaking product an infrastructure layer matched to media-generation latency and quality requirements. The platform supports a multi-stage creative pipeline: users describe a story, the system generates outlines and scripts, builds role settings and storyboards, then moves into image generation, voice-over, music and video production. Baidu's contribution is the real-time cloud backbone that keeps those generation stages responsive enough for iterative work, including the GPU-oriented infrastructure needed for rendering, quality algorithms that check assets across the pipeline and the large-model platforms that help coordinate script and content-generation workflows. Instead of treating film generation as a loose collection of separate AI tools, FilmAction presents the user with one coherent workflow that mirrors traditional production steps while outsourcing the heaviest compute demands to Baidu's cloud environment. This lowers the barrier to cinematic content production and lets the company ship creator-facing experiences at product speed.

Data flow

User prompts enter the FilmAction workflow, where model services generate scripts and storyboards, then cloud rendering and media-generation stages create images, narration, music and video assets that are checked and returned to the creator interface.

Solution architecture

3 components · 2 layers
  1. Compute
    • Qianfan ModelBuilder Provides the large-model environment used for script and content-generation functions.
    • BaiGe AI Heterogeneous Compute Platform Supplies the GPU-oriented infrastructure that keeps generation responsive across stages.
  2. Orchestration
    • Qianfan AppBuilder Packages the creator-facing workflow that spans script, storyboard and media generation steps.

Architecture clues

  • Quality algorithms are used across stages to protect output quality
  • The service is already deployed into Lenovo AI PC notebooks
  • The workflow mirrors traditional film production from outline to final media

Evidence from the source

FilmAction.ai is positioned as the country's first one-stop AI movie-generation platform and is already available on Lenovo AI PC notebooks (original: FilmAction.ai是国内首个一站式AI电影生成平台……目前已在联想AI PC笔记本上线).
Traditional creative flows can be compressed from weeks to minute-level delivery (original: 传统数周的创作流程压缩至分钟级交付).
Users can complete outlines, character settings, script generation, storyboards, dubbing and music from a single platform (original: 只需简单一句话即可完成故事大纲、角色设定、脚本生成、分镜制作、旁白配音和配乐等环节).
Transparency Evidence & methodology 75/100 reference value · 82% confidence · 1 source

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value75/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth25/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity20/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact0/25
    0 metrics describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence82%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability21/25
    10 of 12 key fields link to a named source.
  • Direct evidence15/20
    3 direct source quotes retained.
  • Date provenance10/10
    The publication date comes from the source page or publisher.
  • Source transparency8/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity8/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. Baidu AI Cloud

    Hanhao Technology (FilmAction.ai) customer story

    First-party
    https://cloud.baidu.com/customer/case/filmaction.html
    Source type
    Vendor-published customer story
    Published
    Jun 18, 2025
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes
    • Publication date

Date evidence

  • Published on source page Jun 18, 2025 · Baidu AI Cloud · First-party
    Open date source
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.