Definition
An AI agent pattern that answers complex questions through iterative search-read-compute loops, where each cycle refines the query based on previous findings until the question is sufficiently answered or a budget limit is reached.
In Depth
Deep research agents move beyond single-query search to perform multi-step investigation. The pattern: (1) decompose a complex question into sub-questions, (2) search for each sub-question, (3) read and extract relevant information, (4) compute whether the answer is sufficient or more research is needed, (5) generate refined follow-up queries based on gaps, (6) repeat until confident or budget-exhausted. A typical deep research task like 'compare SERP API pricing for enterprise use in 2026' might execute 15-30 search queries across multiple cycles. Cycle 1 searches broad terms (serp api pricing 2026), extracts provider names and rough pricing. Cycle 2 searches each provider specifically (dataforseo pricing, serpapi enterprise plan). Cycle 3 fills gaps (does serper offer enterprise SLA, scavio growth tier limits). The search-read-compute loop requires three tool capabilities: search (discover relevant pages via API), read (extract content from discovered URLs), and compute (LLM reasoning over collected data to identify gaps and synthesize findings). Tool selection per step: search via Scavio ($0.005/query) or Serper ($0.001/query) for discovery, read via Firecrawl ($0.005-$0.05/page) or Scavio extract for content, compute via Claude or GPT for reasoning. Cost per deep research task: 20 search queries x $0.005 + 10 page reads x $0.01 + 5 LLM compute calls x $0.02 = $0.30 total. Budget management is essential: set maximum queries per research task (e.g., 50), implement diminishing-returns detection (stop when new queries return mostly seen information), and cache results to avoid re-querying the same URLs. The MCP protocol simplifies deep research agent construction by providing search and extraction as standard tools the LLM can invoke natively, reducing custom orchestration code.
Example Usage
The deep research agent received the question 'which SERP API is cheapest for 500k monthly queries across Google and Amazon?' and executed 23 search queries across 4 cycles, ultimately comparing DataForSEO queue mode, Serper bulk packs, and Scavio Growth tier with a cost breakdown table.
Platforms
Deep Research Agent is relevant across the following platforms, all accessible through Scavio's unified API:
- YouTube
Related Terms
Agent Search Budget
A configurable limit on the number of search API credits an AI agent can consume per task, session, or time period, prev...
Content Grounding
The practice of anchoring AI-generated content in verified, real-time data sources so that every factual claim (prices, ...
Agent-First Search
The design philosophy of building search APIs and data formats optimized for AI agent consumption rather than human brow...