When people cannot find what they need, the product feels broken no matter how good the rest is. Good search is an infrastructure problem and a relevance problem at once, and semantic search adds a third dimension when queries are questions rather than keywords.
We build search platforms and the data pipelines that feed them: indexing, classification, extraction, translation and summarization at volume, with quality checks and monitoring built in.
How we approach it
Search is measured, not guessed: we define what a good result looks like for real queries, build, measure and tune. Data pipelines are designed to be re-runnable and observable so a bad batch never poisons the index.
What is included
- Search architecture and indexing pipeline
- Relevance, facets and ranking
- Semantic and hybrid search
- Classification, extraction and summarization pipelines
- Quality checks and monitoring
What you get
Results people trust, in milliseconds Search that understands questions, not only keywords Information processed at a scale people cannot