Scavio for Local RAG + Search API Hybrid Application

The Problem

Pure local RAG returns stale results when the underlying documents are outdated. Pure API RAG has per-query costs and latency. A hybrid approach uses the local index for common queries (fast, free) and falls back to live search for novel or time-sensitive queries (fresh, accurate).

How Scavio Helps

• Local queries are free and fast (no API call)
• API fallback ensures freshness for time-sensitive queries
• Confidence threshold triggers fallback automatically
• Privacy-sensitive queries stay local
• Search API costs only incurred when local index is insufficient

Relevant Platforms

Quick Start: Python Example

Here is a quick example searching Google for "User asks 'What is the current Python version?' Local RAG returns 'Python 3.12' (indexed 6 months ago, stale). Confidence score is low. Fallback triggers: Scavio Google search 'current Python version 2026'. Returns 'Python 3.14 (released March 2026)'. Fresh result served, local index updated.":

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 RAG application developers, teams building knowledge bases, developers using LLMSearchIndex or similar local indices

Scavio handles the search infrastructure — proxies, CAPTCHAs, rate limits, and anti-bot detection — so you can focus on building your local rag + search api hybrid application solution. The API returns structured JSON that is ready for processing, analysis, or feeding into AI agents.

Start with the free tier (500 credits/month, no credit card required) and scale to paid plans when you need higher volume.