Jobs to Be Done
- Build evidence packs for industry and company deep dives
- Track narrative shifts for sectors and public companies
- Monitor regulator, analyst, and executive mentions in news and video
- Source quotes and primary links for reports and investor notes
- Export structured research feeds into knowledge bases
Common Workflows
Deep-dive evidence pack
For each covered company the analyst runs a Scavio batch covering 80 search queries, 50 news queries, and 20 YouTube queries. Results drop into a Notion database with dedup, tagging, and sentiment so the final report pulls straight from a structured evidence table.
Example: scavio.batch(company_queries, platforms=['google','news','youtube']) -> notion
Narrative tracker
A daily job pulls Google News headlines and YouTube video titles for 30 tracked sectors, embeds and clusters them, and flags new narrative clusters that did not exist last week. The analyst receives a ranked briefing on emerging themes before the market reacts.
Example: scavio.google_news(sectors, recency='24h') -> embed -> cluster -> brief
Executive media radar
Scavio monitors 200 named executives across News and YouTube. Any new interview, keynote, or controversy triggers an alert with transcript excerpts and source links, feeding directly into the analyst's research CRM for later citation in reports.
Example: scavio.google_news('"CEO Name"') + scavio.youtube('CEO Name') -> crm.alert
Pain Points Scavio Solves
- Research databases are expensive and lag breaking news
- Manual news scanning burns a full analyst day per week
- Transcripts and video evidence live outside normal research tools
- Hard to get exportable, citation-ready source lists
Tools Research Analysts Pair With Scavio
Notion, Bloomberg Terminal, Perplexity, Obsidian, Google Sheets, Readwise. Scavio returns structured JSON that fits into any of these tools.
Quick Start
import requests
response = requests.post(
"https://api.scavio.dev/api/v1/search",
headers={"x-api-key": "your_scavio_api_key"},
json={"query": "scavio.google_news('semiconductor export controls', recency='24h')"},
)
data = response.json()
# Analyze results for your workflow
for result in data.get("organic_results", [])[:10]:
print(result["title"], "-", result["link"])Platforms You Will Use
Google News
News search with headlines and sources
Web search with knowledge graph, PAA, and AI overviews
YouTube
Video search with transcripts and metadata
Community, posts & threaded comments from any subreddit