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Pure local RAG returns stale results when the underlying documents are outdated.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 (50 credits on signup, no credit card required) and scale to paid plans when you need higher volume.