A1 — APPLIED AI · ENGINEERING

We build AI that ships.And the source stays with your team.

We deliver applied AI systems, workflow upgrades, and the software around them for growing companies. From scoping and proof of concept to tuning and launch support, we ship production systems with full source handover.

Review shipped work →
AI systems / shipped
30
source handover / delivery
500
response kickoff / time
100
working mode / pairing
7
CAPABILITY LEDGERv1.0 · ready for delivery
  • LLMModel applicationsGPT / Claude / Qwen / DeepSeek
  • RAGKnowledge retrievalVector search + access control
  • AGTAgent systemsMulti-step reasoning / tool use
  • WFLWorkflow automationProcess automation / system orchestration
  • VISVision systemsQA / OCR / image analysis
  • ASRVoice and multimodalASR / TTS / video understanding
  • § 01No AI hype callsno hype
  • § 02Ship AI that worksship it
  • § 03Keep the source in-houseno lock-in

DELIVERY MANIFESTO · 2026

Treat AI as an operating capability, not a one-off demo.

These four tracks answer one practical question: how to fit AI into existing systems and keep improving it after go-live. Their order reflects where delivery demand has been strongest lately.

§ 01AID
PRIMARY · AI

Applied AI systems

We build production AI products for live operations: knowledge assistants, copilots, support automation, content workflows, and analysis tools.

Key layers
Foundation modelsRAGAI agentsPrompt systems
  • AI Module
  • 01Model routing
  • 02Knowledge retrieval
  • 03Quality evaluation
  • 04Private deployment
§ 02AIX
PRIMARY · AI

AI workflow transformation

We retrofit AI into operations, customer support, sales, and quality flows so existing systems can run with AI inside the loop.

Key layers
Workflow redesignSupport automationAI workflowFeedback loop
  • AI Workflow
  • 01Workflow audit
  • 02Node redesign
  • 03Closed-loop data
  • 04Continuous tuning
§ 03DEVSUPPORT

Delivery software

We build the surrounding web apps, dashboards, mini-programs, and operations systems that make AI usable in day-to-day work.

WebMini appsOps systems
§ 04SRCSUPPORT

Source-ready products

We deliver reusable source packages for AI assistants, knowledge systems, and SaaS operations so teams can start from a working base instead of rebuilding everything.

Source handoverAI templatesSecond-stage build

Scroll through the AI systems we are shipping.

The stack reveals each case in sequence: problem, solution, value, and delivery signal.

Browse five representative cases with the problem, delivery approach, and outcome in one view.

Enterprise servicesai-transformation
#2d5bff

AI knowledge assistant for enterprise teams

Repeated support load dropped and the team turned static documentation into reusable AI-ready knowledge.

Problem
Operational knowledge lived across scattered docs, and both new hires and support teams kept repeating the same questions.
Approach
We indexed policy and product material into a permission-aware retrieval layer and shipped a RAG assistant on top of it.
Manufacturingai-development
#2d5bff

Computer vision quality inspection for manufacturing

Defects surfaced earlier, audit trails became usable, and quality owners could see line performance in real time.

Problem
Manual inspection was slow, misses were hard to trace, and defect records lived in disconnected spreadsheets.
Approach
We combined visual inspection models with rule-based review and built a line-side dashboard for operators and managers.
Customer serviceai-development
#2d5bff

AI support and ticket collaboration system

Standard questions are answered automatically, complex issues enter the ticket queue, and managers can review recurring issues to improve the knowledge base.

Problem
Support agents switched across tools, repeated the same answers, and lacked a clean handoff and follow-up workflow for complex issues.
Approach
We built AI answering, ticket routing, cited knowledge sources, and human takeover into one support workspace.
Healthcaresoftware-development
#2d5bff

Home nursing appointment service platform

Service delivery is standardized with traceable records for nurses, users, and the platform, supporting category expansion.

Problem
Home nursing involves appointment booking, nurse qualifications, care records, risk notices, and payments, making offline management hard to scale.
Approach
We built user booking, nurse acceptance, service records, electronic agreements, reviews, and admin review workflows.
Commercesoftware-development
#2d5bff

Multi-merchant commerce and settlement system

The platform can run merchant onboarding and operations centrally while merchants manage their own products and orders, with rule-based commission and reconciliation.

Problem
The platform needed to manage merchants, products, orders, after-sales, and commission settlement, which a single-store architecture could not support.
Approach
We separated platform, merchant, customer, and operator roles, then built product, order, settlement, after-sales, and operations dashboards.
CASE / ai-transformationEnterprise services
#2d5bff

AI knowledge assistant for enterprise teams

Problem
Operational knowledge lived across scattered docs, and both new hires and support teams kept repeating the same questions.
Approach
We indexed policy and product material into a permission-aware retrieval layer and shipped a RAG assistant on top of it.
Value
Repeated support load dropped and the team turned static documentation into reusable AI-ready knowledge.
RAGVector searchSupport automationAccess control
answer time < 3sView case
CASE / ai-developmentManufacturing
#2d5bff

Computer vision quality inspection for manufacturing

Problem
Manual inspection was slow, misses were hard to trace, and defect records lived in disconnected spreadsheets.
Approach
We combined visual inspection models with rule-based review and built a line-side dashboard for operators and managers.
Value
Defects surfaced earlier, audit trails became usable, and quality owners could see line performance in real time.
CASE / ai-developmentCustomer service
#2d5bff

AI support and ticket collaboration system

Problem
Support agents switched across tools, repeated the same answers, and lacked a clean handoff and follow-up workflow for complex issues.
Approach
We built AI answering, ticket routing, cited knowledge sources, and human takeover into one support workspace.
Value
Standard questions are answered automatically, complex issues enter the ticket queue, and managers can review recurring issues to improve the knowledge base.
RAGTicket客服工作台Knowledge base
auto-answer rate 68%View case
CASE / software-developmentHealthcare
#2d5bff

Home nursing appointment service platform

Problem
Home nursing involves appointment booking, nurse qualifications, care records, risk notices, and payments, making offline management hard to scale.
Approach
We built user booking, nurse acceptance, service records, electronic agreements, reviews, and admin review workflows.
Value
Service delivery is standardized with traceable records for nurses, users, and the platform, supporting category expansion.
上门医护预约服务记录资质审核
6-step service loopView case
CASE / software-developmentCommerce
#2d5bff

Multi-merchant commerce and settlement system

Problem
The platform needed to manage merchants, products, orders, after-sales, and commission settlement, which a single-store architecture could not support.
Approach
We separated platform, merchant, customer, and operator roles, then built product, order, settlement, after-sales, and operations dashboards.
Value
The platform can run merchant onboarding and operations centrally while merchants manage their own products and orders, with rule-based commission and reconciliation.
多商户订单系统分账运营后台
4 role groups supportedView case

Less packaging. More things you can actually review.

This is built for companies that want AI in production, want the source code in hand, and expect to keep iterating after launch.

  1. 01

    AI that fits operations

    We wire models, retrieval, agents, and automation into real systems and stay accountable for output quality and operating cost.

    30+ systemsdelivers
  2. 02

    100% source handover

    We hand over the application code, prompt systems, and surrounding business logic so your team can keep extending it later.

    ZIP / Gitships
  3. 03

    Fast delivery rhythm

    We keep communication direct, work in short loops, and run the same delivery cadence for remote teams across Asia.

    APACops
  4. 04

    Direct technical pairing

    Technical leads stay in the conversation and help you make grounded calls on feasibility, budget, and rollout timing.

    1 × 1pair
→ Delivery pathDELIVERY PIPELINE
  1. 01Define the operating target

    We clarify the business outcome, the available data, the likely model stack, and what AI should or should not own.

  2. 02Map the workflow and prototype

    We break down prompts, retrieval, agent logic, and integration points into a workable proof of concept.

  3. 03Build and integrate

    We connect models, tune outcomes, build the surrounding application layer, and hand over deployment-ready source code.

  4. 04Launch and iterate

    After launch we monitor quality, refine prompts and data, and support the next layer of extension work.

Articles

Notes on applied AI development, enterprise transformation, delivery methods, and case reviews.

Article content will be added into this home section.

COMPANY FILE / HANGZHOU

A Hangzhou technology company delivering mobile internet and applied AI systems

Founded in 2016, Chengshi focuses on mobile internet application development, applied AI integration, apps, WeChat official accounts, mini programs, websites, and reusable industry software systems.

Its self-developed mobile healthcare platform Anxinhu covers nurse home visits, chronic disease care, home-based elderly care, and related information services.

  • National High-tech Enterprise
  • Zhejiang Contract-honoring Enterprise
  • Hangzhou Major Technology Innovation Project
  • MLPS Level 3 Assessment
  • ISO27001 Information Security
  • Cybersecurity Emergency Support Unit
COPYRIGHT WALL

Software Copyright Gallery

SYSTEM LIBRARY

Ready Systems and Industry Solutions

Reusable systems across commerce, local services, crowdsourcing, operations, and AI tools can be delivered as source packages or customized builds.

01

AI & Content Tools

AI Q&A, image generation, rewriting, and business-system integration.

  • AI智能问答工具系统
  • AI绘画系统
  • AI伪原创系统
  • 信息付费系统
  • 知识付费系统
02

Commerce & New Retail

Multi-merchant, single-store, distribution, rebate, short-video commerce, and group-buy systems.

  • 多商户电商系统
  • 单商户电商系统
  • 各类电商系统
  • 短视频电商系统
  • 抖音电商返利系统
  • 淘宝客系统
  • 拼多多返利小程序
  • 京东返利小程序
  • 社区团购系统
  • 新零售系统
  • 盲盒商城系统
  • 农产品系统
  • 校园购物通系统
03

Local Life & On-demand Services

Delivery, errands, booking, home services, medical care, escort care, and driver dispatch systems.

  • 外卖跑腿系统
  • 外卖点餐系统
  • 同城外卖系统
  • 校园外卖系统
  • 同城跑腿系统
  • 校园跑腿系统
  • 承势代驾系统
  • 承势陪诊系统
  • 上门医护系统
  • 上门回收系统
  • 上门私教系统
  • 上门茶艺系统
  • 上门做饭系统
  • 上门洗车系统
  • 上门预约洗鞋系统
  • 家政服务系统
  • 预约服务系统
  • 月嫂服务系统
  • 鲜花店预约系统
  • 露营基地预约系统
04

Transactions, Settlement & Operations

Payment, verification, reviews, points, settlement, commission, flexible labor, and operations systems.

  • 支付系统
  • O2O核销系统
  • 好差评系统
  • 积分系统
  • 积分分佣系统开发
  • 商城分账分佣系统开发
  • 财务记账分账软件开发
  • 灵活用工系统开发
  • 分销会员系统
  • 会员制度管理系统
  • 招聘系统
05

Tasks, Crowdsourcing & Communities

Task bounty, crowdsourcing, part-time work, community services, gaming companion, and shared device platforms.

  • 任务系统
  • 任务兼职系统
  • 任务悬赏系统
  • 众包接单系统
  • 众包兼职系统
  • 社区兼职系统
  • 同城服务系统
  • 同城服务躲猫猫系统
  • 陪玩系统
  • 游戏陪玩系统
  • 共享无人系统
  • 线上云酒馆系统
  • 霸王餐系统
  • 外卖红包系统
  • 承势短剧系统
DELIVERY TEAM

8-person Delivery Team

Product, design, frontend, backend, mobile, AI, QA, and operations work together with clear ownership from scoping to launch.

Zhou Jun avatar

Zhou Jun

Principal / Delivery Lead

Product Lead avatar

Product Lead

Product Planning

AI Engineer avatar

AI Engineer

AI Application Development

Backend Engineer avatar

Backend Engineer

Backend Architecture

Frontend Engineer avatar

Frontend Engineer

Web / H5 / Admin

Mobile Engineer avatar

Mobile Engineer

App / Mini Program

QA Engineer avatar

QA Engineer

Quality Assurance

Ops Support avatar

Ops Support

Deployment & Security

ECOSYSTEM

Partners

  • 阿里巴巴
  • 腾讯
  • 字节跳动
  • 华为
  • 百度
  • 小米
  • 网易
  • 快手
  • 蚂蚁集团
  • 微信
  • 淘宝
  • 阿里云
  • 携程
  • 大疆
  • 豆瓣
  • 联想
  • 哔哩哔哩
  • 中国东方航空

Start with the operating problem. We can unpack the rest together.

You do not need a polished brief. Share the business goal, the current system, and the timeline you have in mind, and we will help judge whether the right shape is an assistant, a knowledge system, an AI workflow, or a source-ready build.

Phone15168269848
Delivery baseHangzhou, China · Remote delivery across APAC
Emailcontact@chengshi.ai

After submission, your brief is copied and the phone link opens. You can also call 15168269848 directly.