Enterprise Integrations MuleSoft vs Workato: choosing the right integration platform. Two leading integration platforms, very different strengths. Here is how to decide which one fits your enterprise based on complexity, team, and budget. When enterprises ask Valuem which integration platform to use, the honest answer is always: it depends. MuleSoft and Workato are both excellent platforms, but they solve different problems for different organizations. MuleSoft is built for complexity. If you have hundreds of systems, strict governance requirements, custom API strategies, and a dedicated integration team, MuleSoft gives you the control and depth you need. Its Anypoint Platform is enterprise-grade in every sense - API lifecycle management, comprehensive monitoring, granular access controls, and the ability to handle integration patterns that simpler tools cannot. The tradeoff is investment. MuleSoft requires skilled developers, a meaningful learning curve, and licensing costs that reflect its enterprise positioning. For organizations with complex integration landscapes and the team to support it, the investment pays for itself. For smaller integration needs, it can be overkill. Workato takes a different approach. It is designed for speed. Business teams can build integrations using a visual interface, pre-built connectors handle most common SaaS-to-SaaS scenarios, and the platform handles the underlying complexity so your team does not have to. Where Workato excels is in connecting modern SaaS applications quickly. CRM to marketing automation, HRIS to payroll, helpdesk to CRM - these integrations can be live in days, not weeks. The platform also handles workflow automation beyond just data movement, which makes it a strong choice for organizations that want integration and automation in one tool. Here is how Valuem guide the decision. If your integration landscape involves legacy systems, custom APIs, complex transformation logic, and you have or plan to build a dedicated integration team, MuleSoft is the right choice. If your primary need is connecting cloud applications, enabling business teams to build integrations, and moving quickly, Workato is the better fit. Many enterprises Valuem work with use both. MuleSoft handles the core enterprise backbone - ERP, legacy databases, custom applications - while Workato handles the growing ecosystem of SaaS tools that business teams adopt. This hybrid approach gives you the depth where you need it and the speed where it matters. One factor that often tips the decision: AI agent deployment. If you are building AI agents that need to connect to enterprise systems, MuleSoft provides the API layer that agents need to access data securely and reliably. The agent does not connect to the database directly - it connects through a managed API that MuleSoft governs. Enterprise AI agent builder & cloud solutions.

MuleSoft Omni Gateway Support for GraphQL and WebSockets. May 19, 2026 | 8 mins read As part of the recent MuleSoft Omni Gateway announcement, MuleSoft has enhanced API Gateway capability to include support for GraphQL and WebSockets. Modern applications no longer communicate the way they did a decade ago. Today's experiences, AI-powered assistants, collaborative workspaces, live financial dashboards, real-time logistics tracking, are built on two protocols that REST alone simply wasn't designed to handle: GraphQL and WebSockets. Omni Gateway Support for GraphQL and WebSockets. GraphQL lets clients request exactly the data they need, eliminating the over-fetching and chatty round trips that plague complex, multi-domain APIs. WebSockets keep connections open, enabling servers to push updates the moment they happen instead of waiting to be asked. Together, they've become foundational to how developers build responsive, efficient, and connected applications at scale. But as these protocols move from the edge of innovation to the center of enterprise architecture, the platforms that govern, secure, and manage APIs need to keep pace. Omni Gateway delivers on enterprise wide demands for advanced protocol support, AI specific protocols, LLM management, federation enforcement and end-to-end governance. MuleSoft's Anypoint Platform already has a meaningful head start with GraphQL for teams building Mule applications directly with APIkit for GraphQL scaffolds and schema-driven Mule flows to implement queries and mutations at the application layer. These capabilities have helped organizations move toward more efficient, consumer-driven data access. Now with Omni Gateway's new GraphQL and WebSockets support MuleSoft add GraphQL subscriptions, WebSocket transport, gateway-level policy enforcement for native GraphQL traffic. Real-time data, such as live pricing, AI agent streams, collaborative events, IoT telemetry, falls entirely outside what the APIKit handles. Delivering GraphQL and WebSocket protocols enables access to unified, strongly typed heterogeneous sources/servers. What MuleSoft is releasing. GraphQL & WebSockets Protocols are now generally available (GA) on all deployment options of MuleSoft's Omni Gateway, giving developers and administrators powerful solutions for deploying APIs exposing heterogeneous and homogeneous query based resources. The release supports all of the standard GraphQL capabilities: * Queries: Support for fetching data, including features like field selection, arguments, aliases, and fragments * Mutations: Support for performing write operations and state changes, ensuring transactional integrity * Introspection: The ability for clients to query the GraphQL schema for metadata * Directives: Support for standard GraphQL directives (e.g., @skip, @include) The following WebSockets capabilities are now supported: * Real-time Subscriptions: The ability to establish a persistent, bi-directional connection over the WebSockets protocol to enable real-time data push for GraphQL subscriptions * Protocol Compliance: Adherence to common industry specifications (e.g. the graphql-ws protocol) for managing the connection lifecycle (initiation, termination, heartbeat) * Security Context Propagation: Seamless propagation of the client's authentication and authorization context from the initial connection handshake to the subscription processing layer Ensuring essential business value and operational completeness MuleSoft has added 4 key GraphQL policies and a WebSockets policy as well: * GraphQL Schema Validation: Validates incoming GraphQL queries against the API GraphQL schema before forwarding them to the upstream service. This policy is critical to ensuring accurate data access and efficient and meaningful developer feedback on Schema violations * GraphQL Introspection Control: Controls access to the GraphQL introspection system by selectively allowing or blocking __schema, __type, and __typename meta-fields. This policy provides valuable controls around these key query operations * GraphQL Operation Limits: Enforces structural constraints on incoming GraphQL operations to prevent abuse and resource exhaustion. By leveraging maximum depth, maximum aliases, maximum root fields and maximum directives, administrators can put effective guard rails around GraphQL APIs * GraphQL Static Query Complexity: Analyzes incoming GraphQL queries against the API schema to statically calculate their complexity and reject expensive operations before they execute * WebSockets Maximum Connections: Limit the number of simultaneous connections per API MuleSoft Omni Gateway GraphQL and WebSockets demo. Let's look at the MuleSoft Omni Gateway GraphQL and WebSockets solution across Anypoint Exchange and API Manager to see how these services and policies work together: Manage, at scale. GraphQL and WebSocket adoption is accelerating, and so are the operational challenges of managing them at scale. Omni Gateway's new protocols allow organizations protect backends from extensive queries and connection exhaustion; unify governance across REST, GraphQL, WebSocket, gRPC, SOAP, MCP, agents, and LLMs; and deploy in minutes with existing MuleSoft infrastructure with no application code changes.

Automate API Documentation in Exchange across your entire API portfolio. May 15, 2026 | 9 mins read Think about the last time you integrated with an internal legacy service. Did you spend more time building the integration or hunting for the information from the developer who knew which XML tag was mandatory because the documentation was missing? Lack of documentation continues to be the main barrier to asset reuse. Without thorough documentation, even robust APIs stay underused, effectively turning your Exchange catalog into a repository of unused APIs instead of a library of reusable assets. When MuleSoft first launched Generating API Documentation With Einstein Generative AI, MuleSoft addressed the API documentation gap for REST APIs, significantly accelerating the documentation process. To reflect the modern architecture landscape, MuleSoft is pleased to expand its generative API documentation support to protocols such as SOAP, GraphQL, AsyncAPI, gRPC, MCPs and A2A. You can use AI powered capabilities in Exchange to generate documentation for all assets pertaining to above protocols. By broadening its functional capabilities to encompass the full multi-protocol landscape, MuleSoft ensure that your Exchange catalog presents a consistent, comprehensive documentation of all the capabilities, regardless of which protocols your org runs. Protocol-specific intelligence while generating documentation. Documentation needs vary wildly by protocol, and a generic template doesn't work. AI generated documentation now introduces protocol-aware logic: * SOAP: Parses WSDL operations and complex request/response XML envelopes. Documents SOAP actions with appropriate namespaces * GraphQL: Focuses on the graph structures. Documents queries, mutations, and input objects in a way that reflects the hierarchical nature of the schema, not the flat list of the fields * AsyncAPI: Identifies channels and message payload structures for event driven architectures. Makes publishers and consumer relationships explicit, information that was previously buried inside the spec * gRPC: Documents Protobuf definitions, including methods and message types. Clarifies metadata and complex fields to provide transparency into unary and bidirectional streaming patterns * MCP: Documents standardized AI model connections to data sources, systems and applications. Identifies protocol-defined tools, prompts, and resources, so AI agents can seamlessly discover and interact with enterprise data * Agents: Documents AI agent capabilities, tools, skills and orchestration patterns (like Agent-to-Agent). Makes agent behavior discoverable without requiring a conversation with the team that built them Multi-file ingestion solves the context gap. Single-file uploads have always left a context gap while generating the documentation. A spec file that references shared schemas and fragments that live elsewhere in the project will produce incomplete output that misses how the API actually behaves. By leveraging ZIP-based uploads, you can provide an entire specification package including all nested schemas, fragments, and libraries rather than just a single file. Benefits of multi-file ingestion. * Full project awareness: The AI maps relationships across your entire spec package - tracing how a shared RAML fragment or global data type affects endpoints several directories deep, not just the file you uploaded * Coherent documentation, not endpoint lists: With complete project context, the output reads as a logical guide to how your API works, not a disconnected catalogue of routes * No manual gap-bridging: Cross-file references are resolved automatically from the package structure. You don't need to annotate relationships by hand or maintain a separate explanation of how files connect Before you upload your API specification: * Validate your spec first: Broken references or circular dependencies in the ZIP cause the AI to fall back to stable paths only, producing partial output without warning. Run the API Catalog CLI validation step before triggering generation * Clean specs unlock the full context window: A valid specification package allows the AI to use its full LLM context, which directly improves the depth and accuracy of the output Actionable error messages help in resolving issues. Most of MuleSoft have experienced a cryptic 500 error on a Friday afternoon and spent the next hour guessing what went wrong. With this release, MuleSoft replaced ambiguous errors with specific remediation steps when generating documentation. If your Anypoint to Salesforce org connection is misconfigured or if AI document generation hasn't been enabled at the Org level, the platform gives an error message prompting you to contact MuleSoft to enable it. How to enable AI-generated documentation. Before generating documentation, your MuleSoft environment needs two configuration steps. Review the full prerequisites before you begin. 1. Connect your Salesforce Org to the Anypoint Platform. * Go to Anypoint Org settings * Select Salesforce tab from the left panel * Click Add Salesforce Org * Add your Salesforce Org Tenant Key, then click Add 2. Enable Agentforce in your Anypoint org. * In the same Salesforce tab, scroll down to Enhance Anypoint Platform with Agentforce under the Capabilities Managed in Salesforce section * Click Settings * In the pop up, select the Salesforce org you want to enable, click enable Anypoint, and then click Save Make your documentation work for you. The goal isn't more documentation - it's documentation that makes your assets discoverable and reusable. Whether you're covering a SOAP service no one has touched in three years or a new A2A agent shipping next sprint, AI doc generation handles the write-up. You focus on building. To learn more, watch AI-Generated Documentation in Exchange demo and read the Generating API documentation.