AI Sales Automation: Agents vs Workflows

import os, requests, json

SCAVIO_KEY = os.environ["SCAVIO_API_KEY"]
HEADERS = {"x-api-key": SCAVIO_KEY}

def workflow_enrich(lead: dict) -> dict:
    """Deterministic enrichment: always runs the same steps."""
    # Step 1: Search for company info
    company_resp = requests.post(
        "https://api.scavio.dev/api/v1/search",
        headers=HEADERS,
        json={"query": f"{lead['company']} company info", "num_results": 5},
    )
    company_data = company_resp.json().get("organic_results", [])

    # Step 2: Search for tech stack signals
    tech_resp = requests.post(
        "https://api.scavio.dev/api/v1/search",
        headers=HEADERS,
        json={"query": f"{lead['company']} technology stack tools",
              "num_results": 5},
    )
    tech_data = tech_resp.json().get("organic_results", [])

    return {
        **lead,
        "company_snippets": [r["snippet"] for r in company_data[:3]],
        "tech_signals": [r["snippet"] for r in tech_data[:3]],
        "enriched": True,
    }

def agent_qualify(enriched_lead: dict) -> dict:
    """AI agent decides: qualify, nurture, or discard."""
    context = "\n".join(enriched_lead.get("company_snippets", []))
    tech = "\n".join(enriched_lead.get("tech_signals", []))

    # In production, this calls an LLM with the context
    # Here we show the structured decision
    signals = {
        "has_funding": any("raised" in s.lower() or "funding" in s.lower()
                          for s in enriched_lead.get("company_snippets", [])),
        "uses_apis": any("api" in s.lower() for s in
                        enriched_lead.get("tech_signals", [])),
        "team_size_signal": any(word in context.lower()
                               for word in ["hiring", "growing", "team of"]),
    }
    score = sum(signals.values())
    enriched_lead["qualification"] = (
        "hot" if score >= 2 else "nurture" if score == 1 else "cold"
    )
    enriched_lead["signals"] = signals
    return enriched_lead

// n8n Function node: the decision boundary
// Workflow handles: trigger, enrich, store
// Agent handles: qualify, personalize

const lead = $input.first().json;

// Deterministic scoring (workflow territory)
let score = 0;
if (lead.company_size > 50) score += 1;
if (lead.industry === "technology") score += 1;
if (lead.source === "demo_request") score += 2;

// If score is ambiguous (1-2), escalate to AI agent for research
if (score >= 3) {
  return [{ json: { ...lead, route: "fast_track", score } }];
} else if (score >= 1) {
  return [{ json: { ...lead, route: "agent_research", score } }];
} else {
  return [{ json: { ...lead, route: "nurture_sequence", score } }];
}