Ignite Vision

Solution

Ignite Vision built its influencer-matching engine on Alibaba Cloud around a shared data and semantic-understanding layer. PolarDB stores large creator profiles and historical content data, Object Storage Service keeps unstructured campaign briefs and supporting assets, and Elastic Compute Service supplies the elastic application runtime. Qwen provides the multilingual semantic reasoning that converts advertiser requirements and creator characteristics into comparable representations, while Auto Scaling adds capacity when query volumes spike. This arrangement turns a previously manual screening process into a faster retrieval and recommendation workflow: content and profile data are collected from platforms such as Instagram, Facebook, TikTok, and Rednote, normalized into the platform's data store, semantically encoded by Qwen, and surfaced back to marketing teams as searchable, explainable matches. Because Ignite Vision operates across Asian languages and markets, the combination of Qwen's Chinese-language coverage and Alibaba Cloud's cost profile is central to the design.

Data flow

Creator content and brand briefs are gathered from multiple social platforms, stored in PolarDB and Object Storage Service, interpreted semantically by Qwen on ECS, and returned as searchable influencer matches with Auto Scaling maintaining performance during traffic spikes.