Jobs to Be Done
- Discover long-tail content gaps programmatically across thousands of queries
- Fleet-publish content via LangGraph, Mastra, CrewAI, or Hermes Agent loops
- Measure rank on Google organic and in ChatGPT, Perplexity, Claude simultaneously
- Attribute citation changes to content pushes
- Run AEO experiments as first-class SEO tests
Common Workflows
Gap discovery agents
A weekly agent scans Google, Reddit, and YouTube for unanswered or underserved queries in the target niche and produces a content backlog.
Example: for each seed: scavio.google(seed).paa + scavio.reddit(seed) -> backlog
AEO experimentation
Treat content pushes as experiments; track rank in both Google and AI answer engines before and after publish.
Example: scavio.ask('chatgpt', 'best {category}') -> rank_before vs rank_after
Citation-source analysis
Extract and classify which domains each answer engine cites for your queries, then target those domains for mentions.
Example: scavio.ask('perplexity', q).citations -> target_list
Pain Points Scavio Solves
- Traditional SEO tools have no AEO visibility
- Agent loops fail when search tools return inconsistent schemas
- Per-platform auth overhead slows experimentation
- No single metric captures combined Google + AI rank
Tools Agentic SEO Specialists Pair With Scavio
LangGraph, Mastra, CrewAI, Hermes Agent, Ahrefs, Semrush. 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.ask('chatgpt', 'best search api for ai agents')"},
)
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
Web search with knowledge graph, PAA, and AI overviews
Community, posts & threaded comments from any subreddit
YouTube
Video search with transcripts and metadata