Ground Customer Support Agents with Live Search

The Problem

AI customer support agents hallucinate product details, pricing, and policy information because they rely on static knowledge bases that are indexed weekly or monthly. When a product updates its pricing or a policy changes, the agent confidently states outdated information until the knowledge base is re-indexed. Customers receive wrong answers and trust erodes.

The Scavio Solution

Add a live search retrieval step to the support agent's response pipeline. Before answering a product question, the agent queries Scavio's Google endpoint for the current product page or FAQ, then uses the live results as grounding context. This ensures answers reflect today's pricing, features, and policies. The search step adds 1-2 seconds of latency but eliminates the class of errors where the agent states outdated information. Configure the human handoff trigger to fire on low retrieval confidence rather than only on negative sentiment.

Who It Is For

Teams building AI customer support agents that need to answer product, pricing, and policy questions accurately without relying solely on periodically indexed knowledge bases.

Key Benefits

• Real-time product and pricing data in every support response
• Eliminates stale knowledge base hallucination
• 1-2 second latency trade-off for verified accuracy
• Human handoff triggers on low retrieval confidence
• Works alongside existing knowledge base as a verification layer

Python Example

import requests, os
H = {'x-api-key': os.environ['SCAVIO_API_KEY']}
COMPANY_DOMAIN = 'example.com'

def ground_support_answer(question: str) -> str:
    resp = requests.post('https://api.scavio.dev/api/v1/search', headers=H,
        json={'platform': 'google', 'query': f'site:{COMPANY_DOMAIN} {question}'}, timeout=10)
    results = resp.json().get('organic', [])[:3]
    if not results:
        return 'HANDOFF: No live results found, routing to human agent.'
    context = '\n'.join(f"- {r['title']}: {r['snippet']}" for r in results)
    return f"Grounding context from live search:\n{context}"

# Feed this context into your LLM prompt alongside the knowledge base results
print(ground_support_answer('current pricing plans'))

JavaScript Example

const COMPANY_DOMAIN = 'example.com';

async function groundSupportAnswer(question) {
  const resp = await fetch('https://api.scavio.dev/api/v1/search', {
    method: 'POST',
    headers: { 'x-api-key': process.env.SCAVIO_API_KEY, 'Content-Type': 'application/json' },
    body: JSON.stringify({ platform: 'google', query: `site:${COMPANY_DOMAIN} ${question}` })
  });
  const data = await resp.json();
  const results = (data.organic || []).slice(0, 3);
  if (!results.length) return 'HANDOFF: No live results, routing to human.';
  return results.map(r => `- ${r.title}: ${r.snippet}`).join('\n');
}

Platforms Used