Scavio for Stateful Agent Live Data Enrichment

The Problem

Stateful agents accumulate outdated information over long sessions, leading to increasingly inaccurate responses without a mechanism to refresh data.

How Scavio Helps

• On-demand data refresh without session restart
• Structured results integrate cleanly with agent state
• Low cost per refresh keeps long sessions economical
• Platform diversity covers news, discussions, and products
• Simple REST API works with any agent framework

Relevant Platforms

Quick Start: Python Example

Here is a quick example searching Google for "latest LangGraph release features changelog":

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 engineers building stateful agent systems with LangGraph or similar frameworks

Scavio handles the search infrastructure — proxies, CAPTCHAs, rate limits, and anti-bot detection — so you can focus on building your stateful agent live data enrichment 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.