Scavio for AI Trading Multi-Source Data Aggregation

The Problem

AI trading systems that rely on a single data source (news OR social OR commerce) miss signals visible only through cross-source analysis, but integrating multiple data providers creates operational complexity.

How Scavio Helps

• One API key covers news (Google), social (Reddit), commerce (Amazon, TikTok)
• Multi-source signals feed into LLM-based trading analysis
• Unified JSON format simplifies multi-source data pipelines
• Cross-source signal validation improves prediction accuracy
• Per-query pricing scales linearly with trading system complexity

Relevant Platforms

Quick Start: Python Example

Here is a quick example searching Google for "AI trading multi-source data aggregation API news social commerce 2026":

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 Quant teams building multi-signal trading models, fintech startups, and AI-driven trading system developers

Scavio handles the search infrastructure — proxies, CAPTCHAs, rate limits, and anti-bot detection — so you can focus on building your ai trading multi-source data aggregation 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.