Building an entity search product risked slowing core development. A new managed layer powers complex queries, freeing engineers to focus on product.
A search engine built from scratch for AI agents, serving customers from AI-native startups to enterprises by training its own models and indexing billions of web pages.
While the company's core infrastructure handled web search, it was not optimized for a new entity search product. This new vertical required hybrid...
AI-native search engine and API for developers and LLM applications.
Vector database platform for building and scaling AI applications.
Exa's Search for AI agents is part of this use case:
Related implementations across industries and use cases
Similarity search mixed up Q3 and Q4 earnings. Hybrid AI now anchors retrieval with keywords and learns from human fixes instantly.
Manual review of sensitive files took two days. AI agents now finish the work in one hour.
Daily updates delayed new content. A unified database now runs twice-daily refreshes with zero downtime.
Viral spikes forced expensive over-provisioning. Autoscaling AI agents now handle 100k+ weekend runs while curbing idle costs.
Rigid data silos slowed engineering. A unified vector foundation now powers AI agents, accelerating development velocity 4x.
Accountants manually scoured mailboxes to assemble 15 subsidiary workbooks. Now, staff-built AI agents pull invoice data for instant review.
Surging calls caused long holds and overtime. A 24/7 AI voice agent handles routine payroll, freeing 700 HR partners for advisory work.
A 200% yearly data expansion bottlenecked global operations. Now, AI accelerates coding, drafts recipe cards, and resolves inquiries.
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.
Building an entity search product risked slowing core development. A new managed layer powers complex queries, freeing engineers to focus on product.
A search engine built from scratch for AI agents, serving customers from AI-native startups to enterprises by training its own models and indexing billions of web pages.
While the company's core infrastructure handled web search, it was not optimized for a new entity search product. This new vertical required hybrid...
AI-native search engine and API for developers and LLM applications.
Vector database platform for building and scaling AI applications.
Exa's Search for AI agents is part of this use case:
Related implementations across industries and use cases
Similarity search mixed up Q3 and Q4 earnings. Hybrid AI now anchors retrieval with keywords and learns from human fixes instantly.
Manual review of sensitive files took two days. AI agents now finish the work in one hour.
Daily updates delayed new content. A unified database now runs twice-daily refreshes with zero downtime.
Viral spikes forced expensive over-provisioning. Autoscaling AI agents now handle 100k+ weekend runs while curbing idle costs.
Rigid data silos slowed engineering. A unified vector foundation now powers AI agents, accelerating development velocity 4x.
Accountants manually scoured mailboxes to assemble 15 subsidiary workbooks. Now, staff-built AI agents pull invoice data for instant review.
Surging calls caused long holds and overtime. A 24/7 AI voice agent handles routine payroll, freeing 700 HR partners for advisory work.
A 200% yearly data expansion bottlenecked global operations. Now, AI accelerates coding, drafts recipe cards, and resolves inquiries.
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.