Alibaba Cloud Software / SaaS China Translated from Chinese

Yuxun AI Sales Champion System (鱼汛AI销冠系统)

Marketing Personalization · Sales Automation

Yuxun's AI sales-management platform had to run hybrid-LLM workflows, data analysis, model training, and real-time processing across multiple enterprise sales teams, which created strong requirements for elastic compute, secure storage, and privacy protection. The platform also needed to cope with demand spikes during campaigns while keeping sensitive customer and business information protected and auditable.

Reported impact

Business outcome

Alibaba Cloud gave Yuxun a more elastic and secure operating foundation for hybrid-model sales AI. The platform can scale compute around demand surges, protect sensitive enterprise data more consistently, and keep supporting customer-growth and sales-management scenarios without the same infrastructure bottlenecks that would limit a fixed on-premises deployment.

  • Productivity Improvement
  • Risk Reduction
  • Scalability

Solution

Shenzhen Dazhi Software built the Yuxun AI Sales Champion System on Alibaba Cloud as an infrastructure base for AI-assisted sales execution and marketing operations. Customer and team data from work-phone integrations and sales workflows are stored in OSS, where encryption protects datasets used by the application. Elastic Compute Service (ECS) provides the compute layer for data analysis, model training, and real-time processing tasks, so the company can run AI-heavy workloads without pinning them to a fixed server pool. Auto Scaling expands or shrinks ECS instances as user counts and campaign traffic fluctuate. Around that runtime, Web Application Firewall and Security Center add threat defense for internet-facing services and sensitive business information, while Alibaba Cloud's support and compliance posture helps Yuxun operate the platform for enterprise users. The resulting architecture is a cloud foundation for hybrid-model sales automation rather than a generic SaaS deployment.

Data flow

Sales, customer, and work-phone interaction data is stored in OSS, then AI workloads such as analysis, model training, and real-time processing run on ECS. Auto Scaling increases or reduces compute capacity around demand spikes, while WAF and Security Center protect the exposed services and data flows used by the AI sales platform.

Solution architecture

5 components · 4 layers
  1. Compute
    • Elastic Compute Service (ECS) Runs the data-analysis, model-training, and real-time processing workloads behind the Yuxun AI platform.
  2. Storage
    • Object Storage Service (OSS) Stores large volumes of sales and customer data used by the AI sales-management platform, with encryption enabled for stronger protection.
  3. Orchestration
    • Auto Scaling Adjusts ECS capacity as enterprise usage and campaign-driven traffic rise or fall.
  4. Governance
    • Web Application Firewall (WAF) Protects internet-facing services from common web attacks while the platform serves enterprise customers.
    • Security Center Detects and helps defend against security threats affecting the platform and its sensitive data.

Architecture clues

  • Security controls are part of the production design because the application handles sensitive customer and commercial data.
  • The platform integrates Xiaomi and Vivo work-phone capabilities into a broader AI sales-management workflow.
  • The source explicitly describes the workload as including data analysis, model training, and real-time processing on elastic cloud compute.

Evidence from the source

Alibaba Cloud positioned itself as the secure technical partner that helps Yuxun keep growing under competitive pressure. (original: 通过采用阿里云的解决方案,鱼汛 AI 销冠系统不仅能够克服当前面临的业务挑战,还能进一步释放发展潜力,实现持续增长。)
The platform's workload includes data analysis, machine-learning-model training, and real-time data processing, so it needs strong compute elasticity and high availability. (original: 鱼汛 AI 销冠系统涉及大量复杂的 AI 计算任务,包括但不限于数据分析、机器学习模型训练、实时数据处理等,这要求底层云基础设施具备强大的计算能力和高度的灵活性。)
Yuxun is a hybrid-large-model sales system that uses AI to support sales-team management, custom model creation, lead protection, anti-bypass controls, and ad-delivery optimization through Xiaomi and Vivo work-phone integrations. (original: 它是一款基于混合大模型,借助小米和 Vivo 工作手机接口能力研发,通过 AI 赋能销售和营销,集销售团队高效管理、专属大模型打造、客资保护、防飞单、私单,广告投流优化等功能于一体的企业销售 AI 全流程管理系统。)
Yuxun stores large datasets in OSS with encryption, runs compute on ECS, and uses Auto Scaling to add or remove instances as business traffic changes. (original: 鱼汛 AI 销冠系统利用阿里云的对象存储服务 OSS 来存放海量的数据,并启用 OSS 提供的数据加密功能……通过使用阿里云的 Elastic Compute Service(ECS)弹性计算服务……弹性伸缩(Auto Scaling)服务允许系统自动根据业务流量变化来调整 ECS 实例的数量。)
Transparency Evidence & methodology 71/100 reference value · 91% 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 value71/100
  • 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 specificity16/20
    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 confidence91%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability23/25
    11 of 12 key fields link to a named source.
  • Direct evidence20/20
    4 direct source quotes retained.
  • Date provenance10/10
    The publication date comes from the source page or publisher.
  • Source transparency10/10
    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. Alibaba Cloud

    阿里云助力鱼汛 AI 销管系统打造企业销售 AI 全流程系统_互联网与信息技术_阿里云客户案例

    First-party
    https://www.aliyun.com/customer-stories/internet-and-info-tech-2024-yxgzsj
    Source type
    Vendor-published customer story
    Supports
    • Customer
    • Region
    • Company size
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes

Date evidence

  • Published on source page Nov 8, 2024 · Alibaba Cloud · First-party
    Open date source
Not separately sourced Industry, Metrics. Treat these normalized attributes as lower-confidence until a dedicated source is added.