Baidu AI Cloud Software / SaaS China Translated from Chinese

Kingsoft Office

Document Processing

Kingsoft Office wanted to launch a domestic AI office product quickly, but needed a Chinese-first large-model stack, strong content-safety controls and an operating model for continuously tuning prompts and training data across office scenarios.

WPS AI addresses more than 30 common office needs.

Reported impact

Business outcome

Kingsoft launched a domestic AI office assistant that covers multiple content formats, improves user productivity and created an iterative quality-and-safety operating model around office AI.

  • Customer Experience
  • Productivity Improvement
  • Scalability

Solution

Kingsoft Office connected WPS AI to Baidu AI Cloud's Qianfan model platform to create a broad document- and presentation-assistance layer across WPS Office and WPS 365. The technical pattern is a multi-loop operating model rather than a simple API connection. First, an AI-technology middle layer handles large-model API integration, parameters, error codes and quality monitoring. On top of that, prompt engineering defines roles, instruction scopes and chain-of-thought patterns that adapt the model to office tasks. A second loop uses labeled bad cases and SFT data from text, slides and spreadsheets to keep improving output quality. Together those inner and outer loops let Kingsoft co-build and tune office scenarios such as drafting, rewriting, summarizing, polishing, translation and PPT generation, while Qianfan's content-safety controls form a safety boundary around production use. The result is a model-driven office copilot that serves multiple file types and creation stages rather than a single feature.

Data flow

User document, slide and spreadsheet requests flow through WPS AI into the Qianfan model stack, where prompt engineering and labeled training data optimize generation quality before results are returned to office applications.

Solution architecture

4 components · 4 layers
  1. Compute
    • Qianfan Large Model Platform Provides the large-model infrastructure behind WPS AI's writing and presentation features.
  2. Serving
    • WPS AI Delivers user-facing drafting, rewriting, summarization and PPT-generation capabilities.
  3. Orchestration
    • Qianfan AppBuilder Packages the office-assistant experiences across WPS products.
  4. Governance
    • Prompt Engineering Loop Continuously tunes instructions and data to improve office-task quality and safety.

Architecture clues

  • Qianfan safety controls are part of the production architecture
  • The design uses inner and outer optimization loops for prompts and labeled data
  • The same assistant covers text, presentations and spreadsheets

Evidence from the source

Kingsoft connected WPS AI to Baidu's Qianfan platform and quickly launched the first AI office application in China's collaborative-office market (original: 第一时间通过百度智能云千帆大模型平台接入了文心一言,快速推出了 “WPS AI”,这是中国协同办公赛道首个智能办公应用).
The delivery model includes API integration, prompt engineering and labeled-data loops for continuous optimization (original: 第一步是 AI 技术中台接入……第二步是 Prompt 提示词工程……第三步是精标数据驱动).
WPS AI covers drafting, rewriting, summarizing, polishing, translation and PPT generation (original: 包括起草、改写、总结、润色、翻译、续写等……WPS AI 可协助从 PPT 大纲生成、PPT 制作、模板选择、内容修改的全过程).
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

    Kingsoft Office customer story

    First-party
    https://cloud.baidu.com/customer/case/jinshanbangong.html
    Source type
    Vendor-published customer story
    Published
    May 14, 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 May 14, 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.