Solution

Multi-Source Data Aggregation for Trading Research

Independent traders drown in data from a dozen sources: SEC filings, Twitter, Reddit, Bloomberg snippets, YouTube earnings recaps. Each surface is a separate workflow. By the time

The Problem

Independent traders drown in data from a dozen sources: SEC filings, Twitter, Reddit, Bloomberg snippets, YouTube earnings recaps. Each surface is a separate workflow. By the time the trader reconciles them, the signal has decayed.

The Scavio Solution

Build a research agent that calls SERP for filings, Reddit for sentiment, and YouTube for earnings recaps in parallel through one API. Output a typed JSON brief per ticker with five snippets per surface. Trader gets a single daily brief instead of 12 tabs.

Before

12 tabs, manual reconciliation, signal stale by the time the brief is ready.

After

One typed JSON brief per ticker, three surfaces in parallel, ready in seconds.

Who It Is For

Independent traders, small hedge fund analysts, finance Twitter posters, prop-trading research teams.

Key Benefits

  • SERP, Reddit, and YouTube in one credit pool
  • Typed JSON drops into a markdown brief
  • Parallel calls keep latency low
  • Daily brief replaces 12 manual tabs
  • Predictable cost per ticker per day

Python Example

Python
import os, requests
H = {'x-api-key': os.environ['SCAVIO_API_KEY']}

def brief(ticker):
    serp = requests.post('https://api.scavio.dev/api/v1/google',
        headers=H, json={'query': f'{ticker} 10-Q earnings 2026'}).json()
    rdt = requests.post('https://api.scavio.dev/api/v1/reddit/search',
        headers=H, json={'query': ticker}).json()
    yt = requests.post('https://api.scavio.dev/api/v1/youtube/search',
        headers=H, json={'query': f'{ticker} earnings call'}).json()
    return {'serp': serp.get('organic_results', [])[:5], 'reddit': rdt.get('posts', [])[:5], 'youtube': yt.get('videos', [])[:5]}

JavaScript Example

JavaScript
const H = { 'x-api-key': process.env.SCAVIO_API_KEY, 'content-type': 'application/json' };

async function brief(ticker) {
  const [serp, rdt, yt] = await Promise.all([
    fetch('https://api.scavio.dev/api/v1/google', { method: 'POST', headers: H, body: JSON.stringify({ query: `${ticker} 10-Q earnings 2026` }) }).then(r => r.json()),
    fetch('https://api.scavio.dev/api/v1/reddit/search', { method: 'POST', headers: H, body: JSON.stringify({ query: ticker }) }).then(r => r.json()),
    fetch('https://api.scavio.dev/api/v1/youtube/search', { method: 'POST', headers: H, body: JSON.stringify({ query: `${ticker} earnings call` }) }).then(r => r.json())
  ]);
  return { serp, rdt, yt };
}

Platforms Used

Google

Web search with knowledge graph, PAA, and AI overviews

Reddit

Community, posts & threaded comments from any subreddit

YouTube

Video search with transcripts and metadata

Frequently Asked Questions

Independent traders drown in data from a dozen sources: SEC filings, Twitter, Reddit, Bloomberg snippets, YouTube earnings recaps. Each surface is a separate workflow. By the time the trader reconciles them, the signal has decayed.

Build a research agent that calls SERP for filings, Reddit for sentiment, and YouTube for earnings recaps in parallel through one API. Output a typed JSON brief per ticker with five snippets per surface. Trader gets a single daily brief instead of 12 tabs.

Independent traders, small hedge fund analysts, finance Twitter posters, prop-trading research teams.

Yes. Scavio's free tier includes 500 credits per month with no credit card required. That is enough to validate this solution in your workflow.

Multi-Source Data Aggregation for Trading Research

Build a research agent that calls SERP for filings, Reddit for sentiment, and YouTube for earnings recaps in parallel through one API. Output a typed JSON brief per ticker with fiv