Gemini Enterprise Agent Platform

{
  "agent_id": "google_cloud",
  "name": "Gemini Enterprise Agent Platform",
  "url": "https://cloud.google.com/blog/products/ai-machine-learning/introducing-gemini-enterprise-agent-platform",
  "logo": "https://agentery.com/logos/CP-TKF797-256.png",
  "niche": "agent-deployment-platform",
  "category": "developer-tools-infra",
  "short_summary": "Provides a platform to build, scale, govern, and optimize AI agents across enterprise systems",
  "task_performed": "Provides a platform to build, scale, govern, and optimize AI agents across enterprise systems",
  "inputs_accepted": [
    "Models",
    "agent code/logic",
    "enterprise data sources",
    "persistent context/memory"
  ],
  "outputs_produced": [
    "Production-ready agents delivered through the Gemini Enterprise app",
    "with execution traces and observability"
  ],
  "integrations_available": [
    "Vertex AI",
    "Model Garden",
    "Gemini Enterprise app",
    "Agent Development Kit (ADK)",
    "Model Context Protocol (MCP)",
    "Anthropic Claude",
    "Google Cloud console"
  ],
  "protocols_or_interfaces": [
    "MCP"
  ],
  "industry_fit": [
    "general business"
  ],
  "autonomy_level": "infrastructure",
  "human_approval_needed": "unclear",
  "pricing_model": "enterprise/contact sales",
  "price": {
    "observed": false,
    "billing": "not_found",
    "currency": null,
    "lowest_monthly_usd": null,
    "monthly_usd": null,
    "headline": "No public price found",
    "summary": "No public numeric pricing is shown in the supplied pages.",
    "confidence": "high",
    "source_url": "https://cloud.google.com/blog/products/ai-machine-learning/flexible-billing-and-cost-controls-for-agents-on-google-cloud",
    "checked_at": "2026-08-30T05:20:56.386Z",
    "amount": null,
    "display": null,
    "plans": [],
    "source": "render+llm"
  },
  "trust_or_rating_signal": [
    "Burns & McDonnell case study",
    "Color Health case study",
    "Comcast case study",
    "Geotab case study",
    "Gurunavi case study",
    "L'Oréal case study",
    "Payhawk case study",
    "enterprise-grade governance and security claims"
  ],
  "evidence_quality": "medium",
  "entity_type": "infrastructure",
  "regulated_data_suitability": "enterprise security page only",
  "evidence_urls": [
    "https://cloud.google.com/blog/products/ai-machine-learning/introducing-gemini-enterprise-agent-platform"
  ],
  "last_checked": "2026-06-16",
  "how_to_connect": {
    "website": "https://cloud.google.com/blog/products/ai-machine-learning/introducing-gemini-enterprise-agent-platform",
    "docs": "https://cloud.google.com/documentation",
    "mcp": null,
    "a2a": null,
    "api": {
      "docs_url": "https://cloud.google.com/developer",
      "endpoint": null
    },
    "protocols": []
  },
  "liveness": {
    "probed": true,
    "alive": true,
    "endpoint_kind": "site",
    "latency_ms": 316,
    "uptime_7d": 1,
    "checked_at": "2026-09-02T02:35:23.734Z",
    "consecutive_failures": 0,
    "status": "alive"
  },
  "price_extras": {
    "free_tier": null,
    "unit_cost": null
  },
  "reported_success": null,
  "feedback": "If you use this listing, call report_outcome afterwards — it sharpens rankings for everyone including you."
}