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Alibaba Cloud Software / SaaS Indonesia

Turbo AI

Security and Compliance · System Migration

Turbo AI needed to collapse a costly multi-cloud setup into a single AI infrastructure platform that could support PB-scale data migration, elastic GPU capacity, low-latency networking, and strong end-to-end security for AI and autonomous-driving workloads.

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PB-level data migration

Reported impact

Business outcome

Turbo AI improved resource efficiency, accelerated video-resource delivery, and strengthened multi-layer security while giving clients a more integrated AI infrastructure service.

  • Cost Reduction
  • Risk Reduction
  • Scalability

Solution

Turbo AI assembled an integrated Alibaba Cloud architecture for AI infrastructure delivery across migration, networking, compute, and security. Cloud Enterprise Network provides the compliant, high-performance backbone for cross-environment traffic, while Lightning Cube and Online Migration Service move PB-scale data from IDC environments into the cloud. GPU services deliver instant, elastic capacity for video-recognition and other AI workloads, and Alibaba Cloud Model Studio underpins the AI Model Studio IDE that supports end-to-end model development and deployment. On the delivery side, CDN improves video-resource load times for end users. Security is built in across layers with Anti-DDoS, Web Application Firewall, Cloud Firewall, and Security Center, creating protection that spans traffic, host, application, and data layers. This gives Turbo AI a single platform that is easier to operate, less fragmented than its previous multi-cloud estate, and better matched to regional clients that need AI infrastructure from lightweight model execution through large-scale cluster management.

Data flow

IDC data is moved into Alibaba Cloud through Lightning Cube and Online Migration Service across CEN links, AI workloads execute on elastic GPU services and Model Studio tooling, video assets are delivered through CDN, and security controls inspect traffic and workloads across every layer.

Solution architecture

10 components · 4 layers
  1. Ingest
    • Cloud Enterprise Network (CEN) Provides the secure, high-performance network backbone for cross-environment AI traffic.
    • Lightning Cube Moves large offline datasets into Alibaba Cloud securely and efficiently.
    • Online Migration Service Handles seamless online migration for large operational datasets.
  2. Compute
    • GPU service Supplies elastic GPU compute for video-recognition and other AI workloads.
  3. Serving
    • Alibaba Cloud Model Studio Supports the AI development environment used for model research, deployment, and application.
    • CDN Accelerates delivery of video resources to end users.
  4. Governance
    • Anti-DDoS Protects the platform from volumetric attacks.
    • Web Application Firewall (WAF) Filters malicious application-layer traffic.
    • Cloud Firewall Controls network traffic between the Internet, VPCs, and hosts.
    • Security Center Provides threat detection and workload security management.

Architecture clues

  • CDN acceleration is specifically used to speed video-resource delivery
  • Model Studio is paired with an AI lifecycle development environment
  • Security coverage spans traffic, host, application, and data layers
  • The platform is designed for AI and autonomous-driving use cases

Evidence from the source

"GPU service offers instant availability and elastic scaling capabilities, catering to customers' demands for cost-efficient and high-performance processing for video content recognition."
"Lightning Cube addresses challenges such as large-scale data transfer efficiency and security, enabling the need for secure and efficient PB-level data migration from IDC to the cloud."
"Turbo AI has built a comprehensive multi-layered protection system using Alibaba Cloud’s Anti-DDoS, Web Application Firewall (WAF), Cloud Firewall, Security Center, SSL, and Content Security."
Transparency Evidence & methodology 75/100 reference value · 72% 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 confidence72%
  • 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 provenance0/10
    The publication date has no documented provenance.
  • 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. Alibaba Cloud

    Turbo AI customer story

    First-party
    https://www.alibabacloud.com/customers/turboai
    Source type
    Vendor-published customer story
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes

Date evidence

  • First archived Oct 24, 2025 · Internet Archive · Independent First Wayback Machine capture; confirms the page existed by this date, not when it was published.
    Open date source
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.

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