Resumen
Este flujo de trabajo audits your enterprise infrastructure for AI agent integracion readiness. It verifica si external fuentes de datos son accessible, valida API connectivity, prueba search herramienta disponibilidad, y genera un readiness informe. El salida ayuda enterprise architects plan AI agent deployments by identifying cual datos gaps necesita filling antes de agents go live.
Desencadenador
Manual o quarterly programar
Programación
Semanal Monday 6 AM
Pasos del flujo de trabajo
Define audit scope
Cargar el lista of fuentes de datos, APIs, y capabilities el AI agent va a necesita.
Test external search connectivity
Verify ese el Scavio API es reachable y returning resultados for cada requerido plataforma.
Validar datos formato compatibility
Verificar ese respuestas de API match expected esquemas for downstream agent consumption.
Measure latencia budget
Test respuesta times contra el agent's latencia requisitos for en tiempo real interaction.
Verificar cobertura gaps
Identificar cual datos necesita son no covered by disponible APIs y requiere personalizado soluciones.
Generar readiness informe
Compile audit findings en un structured informe con readiness puntuacion y remediation pasos.
Implementacion en Python
import requests
import json
import time
from pathlib import Path
from datetime import datetime
API_KEY = "your_scavio_api_key"
REQUIRED_CAPABILITIES = [
{"name": "Market Research", "platform": "google", "test_query": "enterprise software market 2026"},
{"name": "Competitor Pricing", "platform": "amazon", "test_query": "project management software"},
{"name": "Industry Content", "platform": "youtube", "test_query": "enterprise AI implementation"},
{"name": "Customer Sentiment", "platform": "reddit", "test_query": "enterprise software review"},
{"name": "Product Availability", "platform": "walmart", "test_query": "office supplies bulk"},
]
MAX_LATENCY_MS = 3000
def test_capability(capability: dict) -> dict:
start = time.time()
try:
res = requests.post(
"https://api.scavio.dev/api/v1/search",
headers={"x-api-key": API_KEY},
json={"platform": capability["platform"], "query": capability["test_query"]},
timeout=15,
)
latency_ms = int((time.time() - start) * 1000)
if res.status_code != 200:
return {**capability, "status": "failed", "reason": f"HTTP {res.status_code}", "latency_ms": latency_ms}
data = res.json()
has_results = bool(data.get("organic"))
within_budget = latency_ms <= MAX_LATENCY_MS
return {
**capability,
"status": "ready" if (has_results and within_budget) else "degraded",
"has_results": has_results,
"result_count": len(data.get("organic", [])),
"latency_ms": latency_ms,
"within_latency_budget": within_budget,
}
except Exception as e:
return {**capability, "status": "failed", "reason": str(e), "latency_ms": -1}
def run():
results = [test_capability(cap) for cap in REQUIRED_CAPABILITIES]
ready = sum(1 for r in results if r["status"] == "ready")
total = len(results)
score = round((ready / total) * 100)
report = {
"audit_date": datetime.utcnow().isoformat(),
"readiness_score": score,
"total_capabilities": total,
"ready": ready,
"degraded": sum(1 for r in results if r["status"] == "degraded"),
"failed": sum(1 for r in results if r["status"] == "failed"),
"details": results,
"recommendations": [],
}
for r in results:
if r["status"] == "failed":
report["recommendations"].append(f"Fix connectivity for {r['name']} ({r['platform']}): {r.get('reason', 'unknown')}")
elif r["status"] == "degraded":
if not r.get("within_latency_budget"):
report["recommendations"].append(f"Optimize latency for {r['name']}: {r['latency_ms']}ms exceeds {MAX_LATENCY_MS}ms budget")
output = Path(f"ai_readiness_audit_{datetime.utcnow().strftime('%Y-%m-%d')}.json")
output.write_text(json.dumps(report, indent=2))
print(f"AI Readiness Score: {score}% ({ready}/{total} capabilities ready)")
for rec in report["recommendations"]:
print(f" - {rec}")
if __name__ == "__main__":
run()Implementacion en JavaScript
const API_KEY = "your_scavio_api_key";
const MAX_LATENCY_MS = 3000;
const REQUIRED_CAPABILITIES = [
{ name: "Market Research", platform: "google", testQuery: "enterprise software market 2026" },
{ name: "Competitor Pricing", platform: "amazon", testQuery: "project management software" },
{ name: "Industry Content", platform: "youtube", testQuery: "enterprise AI implementation" },
{ name: "Customer Sentiment", platform: "reddit", testQuery: "enterprise software review" },
{ name: "Product Availability", platform: "walmart", testQuery: "office supplies bulk" },
];
async function testCapability(cap) {
const start = Date.now();
try {
const res = await fetch("https://api.scavio.dev/api/v1/search", {
method: "POST",
headers: { "x-api-key": API_KEY, "content-type": "application/json" },
body: JSON.stringify({ platform: cap.platform, query: cap.testQuery }),
});
const latencyMs = Date.now() - start;
if (!res.ok) return { ...cap, status: "failed", reason: "HTTP " + res.status, latencyMs };
const data = await res.json();
const hasResults = Boolean((data.organic ?? []).length);
const withinBudget = latencyMs <= MAX_LATENCY_MS;
return { ...cap, status: hasResults && withinBudget ? "ready" : "degraded", hasResults, resultCount: (data.organic ?? []).length, latencyMs, withinBudget };
} catch (e) {
return { ...cap, status: "failed", reason: String(e), latencyMs: -1 };
}
}
async function run() {
const results = await Promise.all(REQUIRED_CAPABILITIES.map(testCapability));
const ready = results.filter(r => r.status === "ready").length;
const score = Math.round((ready / results.length) * 100);
console.log("AI Readiness Score: " + score + "% (" + ready + "/" + results.length + " capabilities ready)");
results.filter(r => r.status !== "ready").forEach(r => console.log(" " + r.name + ": " + r.status + " (" + (r.reason || r.latencyMs + "ms") + ")"));
}
run();Plataformas utilizadas
Búsqueda web con grafo de conocimiento, PAA y resúmenes de IA
Amazon
Búsqueda de productos con precios, calificaciones y reseñas
YouTube
Búsqueda de videos con transcripciones y metadatos
Comunidad, publicaciones y comentarios en hilos de cualquier subreddit
Walmart
Búsqueda de productos con precios y datos de cumplimiento