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 (250 credits/month, no credit card required) and scale to paid plans when you need higher volume.