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Scavio for Financial News Sentiment Dataset Building

Build ML training datasets from financial news articles collected via search API. Gather headlines, snippets, and publication dates for specific stocks, sectors, or market events, then label for sentiment to train financial NLP models.

The Problem

Financial NLP models need large labeled datasets of news articles with sentiment labels. News APIs like NewsAPI charge $449/mo for commercial use. Manual collection does not scale. Search APIs provide headlines and snippets at $0.005/query.

How Scavio Helps

  • Collect financial news headlines and snippets at $0.005/query
  • Target specific stocks, sectors, or event types with precise search queries
  • Historical coverage: search for news from specific date ranges
  • Build datasets of 10,000+ labeled articles for under $50
  • Structured JSON output feeds directly into ML preprocessing pipelines

Relevant Platforms

Google

Web search with knowledge graph, PAA, and AI overviews

Quick Start: Python Example

Here is a quick example searching Google for "AAPL earnings report q1 2026 analysis":

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 Quantitative researchers, ML engineers, and fintech teams building financial sentiment models

Scavio handles the search infrastructure — proxies, CAPTCHAs, rate limits, and anti-bot detection — so you can focus on building your financial news sentiment dataset building 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.

Frequently Asked Questions

Build ML training datasets from financial news articles collected via search API. Gather headlines, snippets, and publication dates for specific stocks, sectors, or market events, then label for sentiment to train financial NLP models. The API returns structured JSON that you can process programmatically or feed into an AI agent for automated analysis.

For financial news sentiment dataset building, use the Google Search endpoint. Each request costs 1 credit.

Yes. Scavio handles all the infrastructure — proxies, rate limits, CAPTCHAs, and anti-bot detection. Paid plans support up to 100K+ credits/month with priority support and higher rate limits.

Absolutely. Scavio integrates with LangChain, CrewAI, LlamaIndex, AutoGen, and any framework that can make HTTP requests. Build an agent that searches, analyzes, and acts on financial news sentiment dataset building data automatically.

Build Your Financial News Sentiment Dataset Building Solution

250 free credits/month. No credit card required. Start building with Google data today.