Scavio for Investment Research

The Investment Research Data Challenge

Investment teams need to track brands, products, sentiment, and competitive dynamics across hundreds of tickers or portfolio companies. The research stack historically means expensive per-ticker platforms plus a pile of manual searches. Teams want a data layer that maps to their existing workflow and scales from a solo analyst to a fund with a quant team.

Built for These Teams

• Long/short equity analysts tracking consumer brands
• VC scouts monitoring portfolio mentions and competitor entry
• Prop-shop researchers running event-driven strategies
• Independent analysts publishing newsletters with structured data

Key Workflows

Why Investment Research Teams Choose Scavio

• Structured signals map to ticker-level dashboards
• Cross-platform coverage eliminates per-source scraping stacks
• Predictable per-call pricing fits fund procurement
• Works with Python, R, and notebook-first research workflows
• Integrates with LangGraph and CrewAI for autonomous research

Quick Start Example

Here is a Python example running a investment research query:

import requests

response = requests.post(
    "https://api.scavio.dev/api/v1/search",
    headers={"x-api-key": "your_scavio_api_key"},
    json={
        "platform": "google",
        "query": "portable blender amazon review count trend",
    },
)

data = response.json()
# Process results for your investment research workflow
for item in data.get("organic_results", data.get("products", []))[:10]:
    print(item)

Platforms You Will Use

Scavio is designed for teams that need reliable, structured data at scale. Start with the free tier, build your workflow, then scale when you are ready. No lock-in. No complicated setup. Read the quickstart to get your API key and first response in under two minutes.