Nango Features

Scales to adapt to rising data volume

Allows users to build and deploy custom integrations for customer-facing applications

Ability for users to offload authentication integration

Compliant with GDPR, HIPPA, and other necessary regulations

Allows users to manage third party application integration

Provides a fully white labelled solution

Provides users with intelligent workflow automation capabilities

Self-service enables a software provider’s customers to easily activate packaged integrations.

Monitoring features, including instrumentation and observability, enable the product team and operations teams to centrally manage all customer integrations.

Notification and alerts are included that empower development teams to manage and push out updates to integrations to across their customer base.

Connects to a wide variety of relevant APIs.

Processes called data for organized use.

Empowers developers to build and use integrations intuitively.

Provides clear, effective documentation for API integrations.

Connects users with professional support teams to troubleshoot and finetune integrations.

Provides public user forums for support questions and help.

Organizations have the ability to integrate applications with third party and/or customer facing applications.

Elastic processing capabilities enable software providers to meet customer integration processing demand.

Platform provides users with prebuilt application connectors and integration workflow automations.

Connectivity APIs can be enabled to allow development teams to directly integrate with applications, databases, and services.

Connects to applications through REST, SOAP, GraphQL, or proprietary APIs, regardless of interface type.

Connects AI agents to third-party applications using standardized protocols such as MCP, A2A, or RPC.

Allows AI agents to dynamically discover available tools and actions at runtime.

Integrates with AI agent frameworks such as LangChain and CrewAI.

Offers software development kits and MCP servers to build custom agent integrations.

Provides a testing environment to validate agent integrations before production deployment.

Logs and displays agent actions for monitoring and auditing.

Manages OAuth credentials and token refresh on behalf of the AI agent.

Restricts agent access to specific tools or data based on assigned roles.

Isolates credentials and data across multiple end users or accounts.

Notifies AI agents of events in connected applications in real time.

Selects the most relevant tool for a task and caches frequently accessed data to reduce latency.

Reduces token usage by optimizing how tool data and results are passed to the LLM.

Automatically retries failed actions to ensure reliable task completion.