Tencent Cloud Software / SaaS South Korea

Cafe24 Corp.

Cafe24 needed to expand the range of enterprise-grade AI models available through its LLM Router without sacrificing availability, performance, or the operational simplicity required to support diverse customer workloads.

Cafe24 has $9.2B in platform GMV.
Cafe24 helps merchants sell across 200+ countries.
Cafe24 supports 2M store brands.
Cafe24 supports 6.2M accounts.

Reported impact

Business outcome

Cafe24 broadened model choice and simplified AI adoption by giving developers and businesses one API path to multiple LLMs, improving resilience and making experimentation, deployment, and AI transformation faster.

  • Productivity Improvement
  • Scalability
  • Speed to Market

Solution

Cafe24 extended its existing LLM Router by integrating Tencent Cloud TokenHub so merchants and developers can reach multiple generative AI models through one control plane instead of wiring each provider separately. Cafe24 LLM Router remains the front door for AI requests, handling unified access, real-time model routing, and automatic failover across supported models. Tencent Cloud TokenHub sits behind that router and exposes multiple leading large language models through a single OpenAI-compatible API, letting Cafe24 broaden the model portfolio without adding one-off integrations for every vendor. This architecture supports AI features across Cafe24's broader commerce ecosystem, including product recommendations, marketing automation, and multilingual store operations, while preserving service continuity and flexible model choice. The result is a more resilient generative AI platform that shortens experimentation and deployment cycles for customers pursuing AI transformation.

Data flow

Cafe24 applications send AI requests to Cafe24 LLM Router, which routes them through Tencent Cloud TokenHub's OpenAI-compatible API to the selected model and fails over in real time when needed before responses return to commerce, marketing, and multilingual storefront workloads.

Solution architecture

2 components · 2 layers
  1. Serving
    • Tencent Cloud TokenHub Supplies multiple leading large language models through a single OpenAI-compatible API.
  2. Orchestration
    • Cafe24 LLM Router Provides unified access, real-time routing, and automatic failover across multiple AI models.

Architecture clues

  • Real-time model routing and automatic failover are built into the request path.
  • The design uses a single OpenAI-compatible API to reach multiple models.
  • The integration is positioned as part of Cafe24's broader LLM Router architecture.

Evidence from the source

Cafe24's LLM Router provides unified access to multiple leading AI models through a single API, with real-time model routing and automatic failover, simplifying AI adoption for developers and businesses.
Tencent Cloud TokenHub provides unified access to multiple leading large language models through a single OpenAI-compatible API.
Through its LLM Router, Cafe24 aims to reduce the complexity of integrating multiple AI providers and provide customers with a flexible AI infrastructure that supports faster experimentation, deployment, and adoption of AI services.
With 2M store brands, 6.2M accounts, and $9.2B in platform GMV, Cafe24 helps merchants sell across 200+ countries with integrated payments, shipping, and multilingual support.
Transparency Evidence & methodology 75/100 reference value · 83% 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 confidence83%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability25/25
    12 of 12 key fields link to a named source.
  • Direct evidence20/20
    4 direct source quotes retained.
  • Date provenance0/10
    The publication date has no documented provenance.
  • 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. Tencent Cloud

    Cafe24 Corp. | Tencent Cloud

    First-party
    https://intl.cloud.tencent.com/customers/detail/3588
    Source type
    Vendor-published customer story
    Supports
    • Customer
    • Region
    • Company size
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • Business outcome
    • Metrics
    • Architecture
    • evidence quotes
Not separately sourced Industry. Treat these normalized attributes as lower-confidence until a dedicated source is added.