Helping consumers conveniently and quickly access product information is crucial for enhancing the shopping experience. With the rise of the Internet and smart devices, consumers can now retrieve product details by photographing the product and submitting it to a query system. However, most existing methods rely on image feature matching, which requires extensive labeled image datasets and incurs high system construction costs. This paper proposes a simple yet effective photo-based product information query solution, consisting of offline and online components. The offline part builds a lightweight text knowledge base from product brand and name data on e-commerce platforms. The online part uses OCR to extract text from the submitted photo, infers the product brand, and generates precise query keywords. Experiments on our prototype validate the effectiveness of this approach.