All case studies
RetailEcommerce

AI Semantic Search for Product Discovery

A subscription-based crafting-commerce platform in the US

Custom semantic search that lifted conversion 30% and serves 100M+ monthly queries at sub-50ms latency.

+30%

Higher conversion rate

40%

More relevant results found

<50ms

Search latency at 100M+ queries/mo

Challenge

Manual content tagging bottlenecks

The subscription-based platform required manual tagging of each image, taking several minutes per asset and a dedicated team. This capped content scalability and created ongoing operational inefficiencies.

Inconsistent data quality and search experience

Manual tagging offered no guarantee of consistency, leading to poor search experiences. Users struggled to find relevant content for their projects, adding friction and reducing subscription renewals.

Domain-specific search requirements

Users needed to search highly specific crafting terminology, copyright content, character names, and nuanced project requirements that generic search engines could not understand.

Scalability at 100M+ queries per month

With more than 100M queries a month and a fast-growing content library, the existing infrastructure could not scale while keeping search quality high and response times under 50ms.

Approach

Custom AI models for domain understanding

We trained specialized deep-learning models on millions of in-house crafting assets to capture nuanced terminology and domain knowledge. Built with Python and PyTorch, the models understand crafting contexts, copyright content, and character names that generic models miss.

High-performance vector search pipeline

We implemented OpenSearch-based vector indexing and similarity queries tuned for rapid recall, letting users find relevant assets 40% more often through semantic understanding rather than keyword matching.

Production-grade AI infrastructure

We deployed on AWS SageMaker with Inferentia chips for low-latency inference at scale, serving hundreds of requests per second at sub-50ms latency and replacing the legacy search engine with no parallel system required.

Continuous optimization framework

We embedded an A/B testing framework for continuous UX improvement, validating search-algorithm changes in real time and keeping the experience and conversion rates improving.

Outcome

Higher conversion and better discovery

The platform achieved 30% higher conversion rates through a dramatically improved search experience. Users find the right assets 40% more often, driving engagement and renewals while the system handles 100M+ queries a month at consistent sub-50ms response times.

Operational efficiency and scalability

Automating content understanding eliminated manual tagging bottlenecks. The solution scales with content growth while maintaining quality, reducing operational costs and freeing specialized teams for higher-value work.

Focus Areas

AI & ML SolutionsSemantic SearchEcommerce

Services Provided

Machine Learning ServicesData EngineeringCloud ServicesAPI Development & Integration

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