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Scavio for Evaluate and Benchmark Agent Search Quality

Systematically evaluate AI agent search tool quality by running standardized test queries and measuring result depth, latency, and relevance. Compare search providers to find the best fit for your agent's domain.

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The Problem

AI agent builders pick search providers based on documentation and pricing but have no systematic way to evaluate result quality for their specific use case. A provider that works well for general queries may fail on domain-specific long-tail queries that the agent handles daily.

How Scavio Helps

  • Standardized test suite measures result depth and latency
  • Domain-specific query coverage testing
  • Compare multiple providers on the same test set
  • Latency percentile tracking (p50, p95, p99)
  • Free tier (250 credits) covers initial evaluation

Relevant Platforms

Google

Web search with knowledge graph, PAA, and AI overviews

YouTube

Video search with transcripts and metadata

Reddit

Community, posts & threaded comments from any subreddit

Quick Start: Python Example

Here is a quick example searching Google for "An agent team evaluates search providers for a legal research agent. They run 50 domain-specific test queries (case law, regulation lookups, legal term definitions) through Scavio and two other providers. Scavio returns 8+ results for 48/50 queries vs 6+ for 35/50 from Provider B. p95 latency: 1,200ms (Scavio) vs 2,400ms (Provider B). The team selects based on coverage and latency data, not marketing claims. 50 test queries covered by free tier.":

Python
import requests

API_KEY = "your_scavio_api_key"

response = requests.post(
    "https://api.scavio.dev/api/v1/search",
    headers={
        "x-api-key": API_KEY,
        "Content-Type": "application/json",
    },
    json={"query": query},
)

data = response.json()
for result in data.get("organic_results", [])[:5]:
    print(f"{result['position']}. {result['title']}")
    print(f"   {result['link']}\n")

Built for AI agent builders evaluating search providers, engineering teams benchmarking tool-call quality, platform teams selecting search APIs

Scavio handles the search infrastructure — proxies, CAPTCHAs, rate limits, and anti-bot detection — so you can focus on building your evaluate and benchmark agent search quality solution. The API returns structured JSON that is ready for processing, analysis, or feeding into AI agents.

Start with the free tier (50 credits on signup, no credit card required) and scale to paid plans when you need higher volume.

Frequently Asked Questions

Systematically evaluate AI agent search tool quality by running standardized test queries and measuring result depth, latency, and relevance. Compare search providers to find the best fit for your agent's domain. The API returns structured JSON that you can process programmatically or feed into an AI agent for automated analysis.

For evaluate and benchmark agent search quality, use the Google Search, YouTube Search, reddit endpoints. Each request costs 1 credit.

Yes. Scavio handles all the infrastructure — proxies, rate limits, CAPTCHAs, and anti-bot detection. Paid plans support up to 100K+ credits/month with priority support and higher rate limits.

Absolutely. Scavio integrates with LangChain, CrewAI, LlamaIndex, AutoGen, and any framework that can make HTTP requests. Build an agent that searches, analyzes, and acts on evaluate and benchmark agent search quality data automatically.

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Google API

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YouTube API

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Reddit API

Community, posts & threaded comments from any subreddit

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Scrape Google with Python

Python tutorial for Google

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Build Your Evaluate and Benchmark Agent Search Quality Solution

50 free credits on signup. No credit card required. Start building with Google, YouTube, Reddit data today.

Get Started FreeRead the Docs
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