Structured vs Semantic Search API

A research agent uses Scavio (structured, $0.005) for factual queries ('Tavily pricing 2026', 'DataForSEO minimum deposit') and Exa (semantic, $0.007) for discovery queries ('emerging patterns in AI agent architecture'). 80% of queries are factual (Scavio), 20% are discovery (Exa). Monthly cost for 5,000 queries: 4,000 x $0.005 + 1,000 x $0.007 = $27/month for hybrid grounding.

Structured vs Semantic Search API is relevant to Google, Amazon, YouTube, Reddit. Scavio provides a unified API to access data from all of these platforms.

Two fundamentally different approaches to search API exist for AI agent grounding. Structured SERP APIs (Scavio, DataForSEO, SerpAPI) query traditional search engines and return the same results users see, structured as JSON. Semantic search APIs (Exa, previously Metaphor) use neural models to find pages conceptually related to a query, even without keyword overlap. Structured search strengths: returns what users actually see in search engines. Includes SERP features: AI Overviews, Knowledge Graph, People Also Ask. Provides ranking positions that reflect real search visibility. Better for factual queries, pricing, product data, and local results. Cost: Scavio $0.005/query, DataForSEO $0.0006-0.002/query. Semantic search strengths: finds conceptually related content that keyword search misses. Better for research, discovery, and finding relevant but non-obvious sources. Neural model understands query intent beyond exact keywords. Content extraction returns full page text. Cost: Exa $7-12/1K queries. When to use structured: agent needs factual data (prices, rankings, business info), agent needs to verify what search engines show, agent needs e-commerce or local data, cost sensitivity (structured is 5-10x cheaper per query). When to use semantic: agent needs to discover tangentially related content, agent is doing open-ended research, agent needs to find pages about a concept when the exact terminology is unknown. Hybrid approach: use structured search for factual grounding (primary) and semantic search for research expansion (secondary). Most agent queries (80%+) are factual and better served by structured search. The remaining 20% of research/discovery queries benefit from semantic search.