Enterprise AI platforms that handle integration and agent orchestration, compared

A service agent that answers a refund question is useful. One that checks the order in the ERP, issues the refund in the payment system, updates the CRM and closes the ticket is the reason companies buy agents. The second agent needs integration as much as it needs a model, and that is the question this comparison answers: which platforms give you both, and how well do the two halves fit together?

The short answer. Eight enterprise platforms handle both. Tray.ai builds agents on the same platform as its integrations, under one governance model. Salesforce, Microsoft and Google pair an agent product with their own integration services, which works best inside their ecosystem. AWS gives engineering teams building blocks. IBM packages prebuilt agents. Workato and Boomi added agent tooling to an integration platform.

The platforms at a glance

Two architectures

Every platform here falls into one of two shapes.

Agents and integration on one platform. The agent calls the same connectors, workflows and permissions as the rest of your automation, so there is one place to grant access, one audit log and one bill. Tray.ai is built this way, and Workato and Boomi have moved toward it from the integration side.

An agent product paired with an integration product. Salesforce (Agentforce with MuleSoft), Microsoft (Copilot Studio with Power Automate) and Google (Gemini Enterprise with Vertex AI and Google Cloud services) each pair two products. Inside their own ecosystem the pairing is strong. Outside it, you are licensing, staffing and governing two products, and the seams show when an agent needs a system the vendor does not own.

The platforms

Tray.ai

Best for: agents that have to act across many systems, under one governance model.

Tray.ai builds agents on the same platform as its 700+ connectors and the workflows your teams already run, so an agent acts through integrations that are already versioned, permissioned and audited. Agents can be composed from sub-agents that share tools and data sources, and Agent Gateway publishes those tools over MCP to whichever AI client your people use. Apollo’s IT agent deflected 40% of tickets in its first two weeks, Life360 runs one master agent over departmental sub-agents across 88M monthly active users, and J.W. Pepper replaced 500+ MCP tools with about 20 governed workflows.

IDC named Tray.ai a Major Player in the IDC MarketScape: Worldwide Agentic AI Platforms 2026 Vendor Assessment, and Gartner named it a Pioneer in the 2026 Emerging Market Quadrant for No-Code Agent Builders.

Trade-offs: Tray starts at $50 a month, and a free trial lets you size your usage. Larger plans are a fixed annual price for your plan and expected usage, with no per-user fees. Inside Salesforce or Microsoft 365 specifically, the native agent products have context a third party does not, and if every agent you plan is a Salesforce or Teams agent, that advantage belongs to them.

Salesforce: Agentforce with MuleSoft

Best for: agents working inside a Salesforce-centric business.

Agentforce has the records, permissions and user session already in place, so service and sales agents inside the CRM have a short path to value. For agents that act outside Salesforce, Salesforce positions MuleSoft for integration and Informatica for data.

Trade-offs: that is three licences for one cross-system agent. Agentforce pricing is published and consumption-based, Flex Credits at $500 per 100,000 with an action costing 20 credits, and MuleSoft is metered separately from $2,000 a month billed annually.

Microsoft: Copilot Studio with Power Automate

Best for: organizations standardized on Microsoft 365 and Azure.

If your people live in Teams and Outlook, Copilot Studio is the shortest route to agents they will use, and identity and licensing are already done. Copilot Studio agents can use MCP servers, and Azure API Management can govern them.

Trade-offs: the deepest connector coverage is for Microsoft’s own apps, and governance spans services: agents in Copilot Studio, workflows in Power Automate or Logic Apps, and MCP policies in API Management, each with its own admin and licence.

Google Cloud: Gemini Enterprise

Best for: Google Workspace and Google Cloud shops.

Gemini Enterprise gives employees prebuilt agents and a no-code agent builder over connected business apps, and engineering teams build custom agents on Vertex AI.

Trade-offs: the Business edition starts at $21 per seat per month, while Standard and Plus are sold through sales, and custom agents add model and compute usage on top. Reaching systems outside Google’s connectors means building on Google Cloud.

AWS: Amazon Bedrock AgentCore

Best for: engineering teams building their own agents on AWS.

AgentCore gives developers the building blocks: a runtime, memory, identity, observability and a Gateway that turns APIs and Lambda functions into MCP tools. It is flexible and priced on consumption with no upfront commitment.

Trade-offs: it is infrastructure, not a finished platform. Your team writes the agents and the integrations, and model inference is billed separately from the AgentCore components.

IBM: watsonx Orchestrate

Best for: IBM-centric enterprises that want packaged agents.

watsonx Orchestrate ships prebuilt agents and integrations for common business apps, and it pairs with watsonx.governance for model governance, which is a real strength in regulated industries.

Trade-offs: IBM publishes its prices, Essentials from $530 a month and Standard from $6,360 a month, and the integration depth for systems outside its catalogue is worth testing against your own stack.

Workato

Best for: teams with an established recipe library that want agents attached to it.

Workato builds agents, which it calls genies, in Agent Studio, and runs MCP servers behind an Enterprise MCP gateway with per-user authorization. Agents that call existing recipes are a short path for a team already invested in them.

Trade-offs: the recipe model that shapes the integration layer also shapes what agents can do through it. Workato publishes self-service Pro from $75 a month and quotes its Enterprise editions.

Boomi

Best for: ERP and EDI-heavy environments.

Boomi builds and governs agents in Agentstudio, and Boomi MCP and AI Gateway puts Boomi and third-party MCP servers in one catalogue. Its SAP, Oracle and EDI depth is genuine.

Trade-offs: API management and data movement arrived through acquisitions announced in 2024, and the Atom runtime is something your team sizes and patches. Boomi publishes a $99 a month Pay-As-You-Go plan and quotes enterprise editions.

How to choose

• Agents that act across many systems, under one governance model: Tray.ai
• Every agent lives inside Salesforce: Agentforce, with MuleSoft for reach
• Your people live in Microsoft 365: Copilot Studio
• You are a Google Workspace and Google Cloud shop: Gemini Enterprise
• Your engineers want to build agents themselves on AWS: Bedrock AgentCore
• You want packaged agents and IBM model governance: watsonx Orchestrate
• You already run a large Workato recipe library: Workato
• ERP and EDI are the centre of gravity: Boomi

Whichever you shortlist, run one real cross-system agent through each, and ask for the cost at your volume in writing, integration layer included. For the case for one platform over a stack of agent tools, see why AI agent orchestration is key to enterprise AI.

Sources

• IDC MarketScape: Worldwide Agentic AI Platforms 2026 Vendor Assessment, #US54140926, 12 October 2026
• Salesforce, Agentforce pricing
• MuleSoft, pricing
• Microsoft, Power Automate pricing and Copilot Studio MCP
• Google Cloud, Gemini Enterprise for business
• AWS, Amazon Bedrock AgentCore pricing
• IBM, watsonx Orchestrate pricing
• Workato, Agent Studio and MCP Gateway
• Boomi, pricing, Agentstudio and Boomi MCP