Agentic AI on Cloud Platforms
AWS, Azure, Google Cloud, and the Enterprise Ecosystem
Key Takeaways
- AWS Bedrock AgentCore launched December 2025 with Policy controls, Memory, and 13 pre-built evaluation systems for enterprise-scale deployments
- Microsoft Azure AI Foundry reached GA at Build 2025, featuring Agent 365 governance and one-click deployment to Teams and M365 Copilot
- Google Vertex AI Agent Builder ADK has been downloaded 7M+ times; Wells Fargo became the first major bank to deploy agentic AI company-wide
- NVIDIA, IBM, Databricks, and Adobe are expanding the ecosystem with specialized inference, orchestration, and experience platforms
CLOUD AGENTIC AI BY THE NUMBERS (2026)
Sources: AWS, Google Cloud, PwC, IBM
Why Cloud Platforms Matter for Agentic AI
The shift from simple chatbots to agentic AI systems that plan, reason, and execute multi-step tasks autonomously has created massive infrastructure demands. Building production-grade AI agents requires sophisticated orchestration, memory management, tool integration, security controls, and observability—capabilities that cloud platforms are uniquely positioned to provide.
In 2025-2026, the major cloud providers—AWS, Microsoft Azure, and Google Cloud—have all launched comprehensive agentic AI platforms. Beyond the hyperscalers, specialized vendors like NVIDIA, IBM, Databricks, and Adobe are building targeted solutions for inference, enterprise orchestration, data intelligence, and customer experience respectively.
The Enterprise Imperative
According to Gartner, 40% of enterprise applications will feature task-specific AI agents by the end of 2026. However, they also predict that over 40% of agentic AI projects will be canceled by 2027 due to escalating costs, unclear business value, or inadequate risk controls—making platform selection critical.
This guide provides a comprehensive comparison of cloud-based agentic AI offerings, covering the hyperscaler platforms (AWS, Azure, Google Cloud) and specialized solutions (NVIDIA, IBM, Databricks, Adobe). We examine features, pricing, integration patterns, and real-world implementations to help you make an informed decision.
Platform Comparison at a Glance
Before diving into individual platforms, here is a high-level comparison of cloud-based agentic AI offerings:
| Platform | Primary Strength | Best For | GA Status |
|---|---|---|---|
| AWS Bedrock AgentCore | Enterprise security, multi-model access | AWS-native enterprises, regulated industries | GA Dec 2025 |
| Azure AI Foundry | M365/Teams integration, Entra governance | Microsoft-centric organizations | GA May 2025 |
| Google Vertex AI | Observability, Gemini integration | GCP users, data-centric workflows | GA Nov 2025 |
| NVIDIA NIM | Accelerated inference, on-prem deployment | High-throughput, GPU-heavy workloads | GA |
| IBM watsonx Orchestrate | Multi-LLM flexibility, pre-built agents | Hybrid cloud, finance/supply chain | GA |
| Databricks Mosaic AI | Data lakehouse integration, MLOps | Data teams, RAG applications | GA |
| Adobe Experience Platform | Customer experience orchestration | Marketing, CX teams | GA Sep 2025 |
AWS Bedrock Agents & AgentCore
Amazon agentic AI infrastructure
Amazon Bedrock Agents enables developers to build AI agents that can orchestrate interactions across multiple foundation models, execute multi-step tasks, and integrate with enterprise systems. At AWS re:Invent 2025, Amazon launched AgentCore—a comprehensive platform for building, deploying, and operating enterprise-scale agents.
AgentCore Components
- •Runtime: Secure, serverless deployment
- •Gateway: Unified tool access and connections
- •Memory: Intelligent context retention across sessions
- •Identity: Authentication across AWS and third-party services
- •Browser & Code Interpreter: Enhanced agent capabilities
December 2025 Updates
- •Policy: Natural language boundaries for agent actions
- •Evaluations: 13 pre-built evaluation systems for quality scoring
- •Episodic Memory: Agents learn from past experiences
- •Observability: Comprehensive monitoring and debugging
AgentCore Pricing
| Component | Price | Unit |
|---|---|---|
| Runtime (vCPU) | $0.0895 | per vCPU-hour |
| Runtime (Memory) | $0.00945 | per GB-hour |
| Gateway - Tool API | $0.005 | per 1,000 invocations |
| Gateway - Search | $0.025 | per 1,000 queries |
| Memory - Short-term | $0.25 | per 1,000 events |
| Memory - Long-term | $0.75 | per 1,000 memories stored |
Source: AWS Bedrock AgentCore Pricing | Policy and Evaluations are free during preview. New customers receive $200 in Free Tier credits.
Real-World Cost Example
Processing 10 million user requests monthly with 60-second sessions, 70% I/O wait time, 1 vCPU during active processing, and memory peaking at 2.5GB:
~$7,235/month
Compute only, plus model inference and storage costs
Best for: AWS-first enterprises and regulated industries requiring VPC isolation, PrivateLink, CloudFormation support, and consumption-based pricing with infrastructure-grade security controls.
Microsoft Azure AI Foundry & Copilot
Microsoft agentic AI ecosystem
Azure AI Foundry Agent Service reached general availability at Microsoft Build 2025, providing a unified platform for building, managing, and scaling AI agents within the Microsoft ecosystem. The platform emphasizes seamless integration with Microsoft 365, Teams, and Copilot, with enterprise-grade security through Microsoft Agent Framework.
Agent 365
Control plane for enterprise agent governance with centralized policy management, monitoring, and compliance
Agent Mode
AI-generated spreadsheets and documents in Excel and Word with autonomous task execution
Office Agent
Powered by Anthropic models for PowerPoint and Word creation in a chat-first experience
Key Features
- •One-click deployment to Teams and M365 Copilot
- •Multi-agent orchestration with real-time debugging
- •MCP and Agent2Agent (A2A) protocol support
- •Model router for dynamic best-fit model selection
- •Both OpenAI and Anthropic models available
Azure Copilot Agents (Preview)
- •Migration Agent: Cloud migration planning
- •Deployment Agent: Infrastructure provisioning
- •Optimization Agent: Cost and performance tuning
- •Observability Agent: Monitoring and alerting
- •Troubleshooting Agent: Issue diagnosis
Pricing & Availability
Azure AI Foundry platform is currently free to explore. Individual features are billed at standard rates. Billing for managed hosting runtime will be enabled no earlier than February 1, 2026.
Azure is the only cloud supporting access to both Claude and GPT frontier models. Anthropic Claude Sonnet 4.5, Opus 4.1, and Haiku 4.5 are available alongside OpenAI models including GPT-5.1.
Sources: Microsoft Ignite 2025, Microsoft Learn
Best for: Microsoft-centric enterprises wanting governed agent building within the Azure/M365 ecosystem with seamless deployment to existing collaboration tools like Teams.
Google Vertex AI Agent Builder
Google Cloud agentic AI platform
Google Vertex AI Agent Builder is a comprehensive suite for building, scaling, and governing AI agents in production. The platform features the Agent Development Kit (ADK), which has been downloaded over 7 million times since launch, and now supports Go in addition to Python and Java.
Agent Engine
Fully-managed runtime for deploying and scaling agents with built-in services:
- •Sessions: Persistent session management (GA)
- •Memory Bank: Topic-based memory across weeks/months (GA)
- •Code Execution: Sandboxed code runner
- •Evaluation: Built-in quality assessment
Tool Governance (Dec 2025)
Cloud API Registry integration for enterprise control:
- •Private registry for approved tools across organizations
- •Pre-built tools for Google services
- •Agent identities tied to Cloud IAM
- •Model Armor for prompt injection protection
Development Tools
Agent Development Kit
Python, Java, and Go SDKs. Deploy with single command: adk deploy
Agent Designer (Preview)
Low-code visual designer for building and testing agents before transitioning to code
Agent Garden
Library of sample agents and tools for customer service, data analysis, creative writing
| Component | Price | Billing Start |
|---|---|---|
| Agent Engine Runtime (vCPU) | $0.00994/vCPU-hour | November 6, 2025 |
| Agent Engine Memory | $0.0105/GiB-hour | November 6, 2025 |
| Sessions, Memory Bank, Code Execution | Variable | January 28, 2026 |
Source: Vertex AI Pricing | Express Mode allows limited free usage (up to 10 agent engines, 90 days). New accounts receive $300 credits.
Best for: Google Cloud users seeking first-party observability, strong Gemini integration (including Gemini 3 Flash and Computer Use), and data-centric workflows.
NVIDIA NIM Microservices
Accelerated inference for agentic AI
NVIDIA NIM (NVIDIA Inference Microservices) provides accelerated inference containers that can run on any NVIDIA GPU—cloud, data center, workstations, or PCs. For agentic AI, NIM combines optimized inference with the NeMo Agent toolkit for building and deploying agents.
Nemotron 3 Family (H1 2026)
Open reasoning models for agentic AI applications:
- •Nemotron 3 Nano: 4x higher throughput than v2, best tokens/sec for multi-agent systems
- •Nemotron 3 Super: Balanced performance (coming H1 2026)
- •Nemotron 3 Ultra: Maximum capability (coming H1 2026)
Enterprise Integrations
- •Microsoft Azure: Llama Nemotron models in Azure AI Foundry
- •SAP: Enhanced ABAP code completion with NIM
- •Cerence: Automotive AI assistants in 2026 vehicles
- •SQL Server 2025: Nemotron RAG integration
Key Differentiator: Deploy Anywhere
NIM microservices provide pre-built containers powered by Triton Inference Server and TensorRT-LLM, reducing deployment times from weeks to minutes. Organizations can run models on-premises for maximum privacy or across any cloud with NVIDIA GPU access.
Best for: Organizations needing high-throughput inference, on-premises deployment options, or those building multi-agent systems at scale with GPU-accelerated infrastructure.
IBM watsonx Orchestrate
Multi-LLM enterprise agent orchestration
IBM watsonx Orchestrate brings AI agents together for collaborative, scalable enterprise automation. Named a Leader in the Gartner Magic Quadrant for AI Application Development Platforms (2025), IBM differentiates through LLM flexibility, pre-built domain agents, and hybrid cloud support.
Platform Capabilities
- 1100+ pre-built agents and 400+ tools for enterprise workflows
- 2AI Gateway: IBM Granite, OpenAI, Anthropic, Google Gemini, Mistral, Ollama
- 3Langflow integration for drag-and-drop visual agent building
- 4AgentOps observability with real-time monitoring and policy controls
Domain-Specific Agents
Finance Agents
Powered by IBM Planning Analytics for forecasting, scenario analysis, and risk assessments
Supply Chain Agents
Integrations with IBM Sterling, SAP, Oracle, Coupa for disruption response
Strategic Partnerships
IBM partnered with Anthropic to provide enterprise access to Claude models within controlled, compliant environments. They also partnered with Groq in October 2025 for high-speed inference via GroqCloud.
IBM has saved $3.5 billion in internal costs using watsonx, including 125,000 hours per quarter in case summarization alone.
Best for: Enterprises seeking LLM flexibility without vendor lock-in, organizations with hybrid cloud requirements, and teams needing pre-built agents for finance or supply chain operations.
Databricks Mosaic AI
Data intelligence platform for agents
Databricks Mosaic AI integrates agentic AI with the Data Intelligence Platform, providing everything needed to deploy end-to-end RAG systems with security, governance, and data integration. At Data + AI Summit 2025, Databricks announced Agent Bricks—a new approach to building high-quality agents auto-optimized on your data.
Agent Bricks
Provide a description and connect data—Agent Bricks handles the rest:
- •Structured information extraction
- •Reliable knowledge assistance
- •Custom text transformation
- •Multi-agent system building
Platform Features
- •MLflow 3.0: Agent observability, prompt versioning, cross-platform monitoring
- •Vector Search: 7x lower cost, billions of vectors at scale
- •MCP Integration: Anthropic protocol directly in platform
- •Unity Catalog: Unified governance for agents and data
Best for: Data teams building RAG applications, organizations with existing Databricks investments, and teams needing unified governance across data and AI assets.
Adobe Experience Platform Agent Orchestrator
Customer experience agentic AI
Adobe Experience Platform Agent Orchestrator is the agentic layer in Adobe Experience Platform, powering purpose-built agents for customer experience orchestration. Announced at Adobe Summit 2025 and reaching GA in September 2025, it enables marketing and CX teams to deploy AI agents with human oversight.
Available Agents
- Audience Agent: Insights, size change detection, duplicate detection
- Data Insights Agent: Natural language analytics in Customer Journey Analytics
- Experimentation Agent: Analyze results, predict impact, propose experiments
- Journey Agent: Create, analyze, optimize customer journeys via NL
Strategic Partnerships
Adobe has partnerships enabling cross-platform agent execution:
Coming Soon: Agent Composer for customization and Agent SDK for developers
Best for: Marketing and CX teams using Adobe Experience Cloud, organizations focused on customer journey optimization, and teams needing multi-channel campaign agents.
Case Study: Wells Fargo & Google Cloud Agentic AI
Wells Fargo
First major commercial bank to comprehensively adopt AI agents
In January 2025, Wells Fargo announced an expansion of their strategic relationship with Google Cloud to deploy agentic AI at scale across the organization. As an early adopter of Google Agentspace, Wells Fargo is equipping employees across all business lines with AI agents.
Use Cases
- •FX post-trade inquiry triage and summarization
- •Policy and procedure navigation across internal systems
- •250,000 vendor agreement documents queried by custom agent
- •24/7 customer service with hyper-personalization
Capabilities Deployed
- •Google Agentspace: Unified agent management platform
- •NotebookLM: Document analysis and insight generation
- •Real-time market insights: For traders and bankers
- •Responsible AI frameworks: Ethical deployment guidelines
Sources: Wells Fargo Newsroom, Banking Dive, PYMNTS
Pricing Comparison
Cloud agentic AI pricing varies significantly by provider and component. Here is a side-by-side comparison of key costs:
| Component | AWS AgentCore | Azure AI Foundry | Google Vertex AI |
|---|---|---|---|
| Runtime (vCPU/hour) | $0.0895 | Free until Feb 2026 | $0.00994 |
| Memory (GB/hour) | $0.00945 | Free until Feb 2026 | $0.0105 |
| Free Tier | $200 credits | Free to explore | $300 credits + Express Mode |
| 10M sessions/month | ~$7,235 | TBD | Variable |
Important: Model Inference Costs Add Up
The prices above cover infrastructure only. Model inference costs (per token/request) are billed separately and often represent the largest portion of agentic AI expenses. Claude, GPT-4, and Gemini each have different pricing that varies by context length and model version.
How to Choose Your Cloud Platform
Selecting the right cloud platform for agentic AI depends on your existing investments, team capabilities, and specific use cases:
Choose AWS if...
- →Your organization is AWS-first with existing VPC, IAM, and infrastructure investments
- →You need enterprise-grade security controls and compliance certifications
- →You want access to Claude, Llama, and Amazon Nova models in one platform
Choose Microsoft Azure if...
- →Your organization uses Microsoft 365, Teams, and Copilot extensively
- →You need one-click agent deployment to collaboration tools
- →You want access to both OpenAI and Anthropic frontier models
Choose Google Cloud if...
- →You prioritize observability and want built-in dashboards for agent monitoring
- →You want deep Gemini integration including Computer Use capabilities
- →You prefer low-code visual tools alongside pro-code SDKs
Consider specialized platforms if...
- →NVIDIA NIM: You need on-premises deployment or maximum inference throughput
- →IBM watsonx: You need LLM flexibility and pre-built finance/supply chain agents
- →Databricks: You have existing data lakehouse investments and need unified governance
- →Adobe: Your focus is marketing and customer experience orchestration
Summary: Cloud Agentic AI Landscape
HYPERSCALER PLATFORMS
AWS Bedrock AgentCore, Azure AI Foundry, and Google Vertex AI provide enterprise-grade infrastructure. AWS excels in security, Azure in M365 integration, Google in observability.
SPECIALIZED SOLUTIONS
NVIDIA NIM for inference, IBM watsonx for multi-LLM orchestration, Databricks for data-centric agents, Adobe for customer experience—each serves specific enterprise needs.
REAL-WORLD ADOPTION
Wells Fargo became the first major bank to deploy agentic AI company-wide via Google Cloud. PwC built 120+ agents across 24 workflows. IBM saved $3.5B internally.
KEY DECISION FACTORS
Existing cloud investments, integration requirements, model access needs, and team capabilities should drive platform selection over pure feature comparisons.
Navigate the Cloud AI Landscape
At Planetary Labour, we help organizations evaluate and implement agentic AI platforms that deliver measurable business outcomes while managing risk.
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