A new startup called Exa is developing an innovative search engine that aims to transform how we find and organize information online by treating the entire internet as a structured database rather than just a collection of web pages.
The technological breakthrough: Exa’s new search engine, Websets, leverages large language models to encode web pages into “embeddings” that capture their underlying meaning rather than just matching keywords.
- The technology creates a semantic understanding of web content, allowing for more precise and relevant search results
- Unlike other AI search engines that simply layer language models over traditional search, Exa has rebuilt the search architecture from the ground up
- The system predicts relevant links by understanding the relationships between different pieces of content across the web
Primary use cases and target audience: Websets is designed specifically for power users seeking structured information that traditional search engines often struggle to provide effectively.
- The platform excels at generating comprehensive lists of companies, people, or other entities that share specific characteristics
- Users can make complex queries that would typically require multiple searches or manual filtering on conventional search engines
- The results are presented in a more organized, database-like format rather than as a simple list of web pages
Current limitations: Despite its innovative approach, Websets faces several significant technical constraints in its current form.
- Search queries can take minutes to process, significantly longer than traditional search engines
- The platform currently indexes only about 1 billion web pages, compared to Google’s trillion-page index
- The system is still being refined and improved as the technology evolves
Market positioning and potential: Exa is positioning itself as a complement to rather than a replacement for existing search engines.
- The company acknowledges its current limitations while emphasizing the long-term potential of its embedding-based approach
- The technology could potentially reshape how specialized searches are conducted in professional and research contexts
- External experts see promise in the approach but note that scaling will be crucial for widespread adoption
Looking ahead: While Exa’s ambitious approach to search represents a significant departure from conventional methods, its success will likely depend on its ability to overcome current performance limitations while maintaining its precision advantage over traditional search engines.
The startup trying to turn the web into a database