The Problem
Open web search returns noisy results from SEO spam sites. Agents need search limited to authoritative sources for reliable grounding.
How Scavio Helps
- Search only trusted domains
- Reduce noise from SEO spam
- Higher signal-to-noise ratio for agents
- Combine curated and open search
- Structured results for efficient token usage
Relevant Platforms
Web search with knowledge graph, PAA, and AI overviews
Community, posts & threaded comments from any subreddit
Quick Start: Python Example
Here is a quick example searching Google for "kubernetes pod autoscaling best practices":
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 Enterprise AI teams deploying production agents
Scavio handles the search infrastructure — proxies, CAPTCHAs, rate limits, and anti-bot detection — so you can focus on building your curated search for agent deployment 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.