Jobs to Be Done
- Build convincing POCs quickly during sales cycles
- Customize search integrations for enterprise pilots
- Debug customer edge cases across geos, devices, and platforms
- Train customer engineers on how to call Scavio from their stack
- Translate customer problems into repeatable workflow templates
Common Workflows
Day-one POC kit
A reusable repo with LangChain, Jupyter, and n8n examples lets an SE spin up a working Scavio integration in under a day for a new prospect. Custom queries, branded schema, and a demo dashboard come preconfigured to shorten the discovery-to-value gap.
Example: git clone scavio-poc && set API_KEY && run notebook -> live demo
Geo and device edge-case debugging
When a customer reports odd results, the SE replays the query through Scavio across 5 geos and devices, logs the exact SERP features returned, and compares against the customer's expected output. Findings ship as a runbook entry so Support can resolve repeats quickly.
Example: for (geo, device) in grid: scavio.google(q, location=geo, device=device) -> report
Workflow template library
Every solved pilot becomes a template (rank tracking, review monitoring, RAG retrieval). Templates live in a customer-facing catalog with diagrams, code, and sample data so new customers self-serve onto the right pattern for their use case instead of starting blank.
Example: scavio.templates.list() -> customer picks 'review_monitoring' -> deploys
Pain Points Scavio Solves
- Every prospect expects a working POC inside a week
- Customer stacks vary wildly and stitching scrapers per deal does not scale
- Hard to reproduce customer-specific SERP bugs without tooling
- Training customer engineers on custom scraping eats cycles
Tools Solutions Engineers Pair With Scavio
Postman, n8n, Jupyter, LangChain, Salesforce, Loom. 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('enterprise crm', location='London', device='desktop')"},
)
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
Amazon
Product search with prices, ratings, and reviews
YouTube
Video search with transcripts and metadata
Walmart
Product search with pricing and fulfillment data
Google Shopping
Shopping results with multi-retailer pricing