The Universal Invocation Layer for AI Agents
One API to run them all. Invoke agents built on any framework: Agno, Strands, LangGraph, or custom implementations, with native support for Streaming (SSE), Sync, and Async execution.
Framework Agnostic
Bring your own agent. Whether you build with Agno, Strands, LangGraph, or custom implementations, wrap them in one standardized API specifically designed for agentic workflows.
Real-Time Streaming (SSE)
Stream responses instantly. Native Server-Sent Events (SSE) support lets you stream thoughts, intermediate steps, and final answers to your UI without latency.
Enterprise Control
Built for scale. Invoked agents run as serverless agents in the cloud, or in your own Kubernetes cluster. Includes managed authentication, PII masking, and audit logs.
How it Works
Pass rich context, user details, and file attachments effortlessly with a simple JSON payload.
Use Cases
Unified Agent Governance
Stop fragmentation. Your data science team uses LangGraph; your engineering team uses AutoGen. The Agents API standardizes the invocation contract across your entire organization.
Powering Custom Experiences
Build AI Assistants, enterprise search systems, or chat interfaces by simply hitting a standard REST endpoint. With native SSE streaming, you can deliver 'Copilot-like' experiences.
Complex Orchestration
Move beyond simple chatbots. Use the API to trigger chain-reactions where one agent's output becomes another's input. Orchestrate multi-step workflows with full visibility.
Frequently Asked Questions
API & Integration
How does the Agents API integrate with existing applications?
The Agents API provides a standard REST endpoint that you can integrate into any application. It supports multiple deployment options including cloud-hosted and self-hosted on your own Kubernetes clusters. The unified integration layer means you can connect agents to customer support tickets, enterprise search, or any custom workflow with minimal code changes.
What monitoring and tracing capabilities are available?
The Agents API includes built-in observability with monitoring and tracing for production workloads. You can track agent execution, view intermediate steps through SSE streaming, and access comprehensive audit logs for enterprise-grade compliance.
What backend services does the Agents API provide?
The Agents API can function as a BaaS (Backend-as-a-Service) for AI agents, handling infrastructure concerns so developers can focus on agent logic. Services include managed scaling, event triggers, observability, and deployment pipelines. The platform integrates with DevOps and MLOps workflows, enabling teams to productionize agents and LLM models using familiar CI/CD practices.
How does the Agents API serve as a control plane for AI agents?
The Agents API acts as a unified control plane for managing AI agents across your organization. Developers can build agents using their preferred frameworks while the platform provides centralized management, scaling, and observability. This enables internal teams and platform architects to maintain governance over all agent deployments without restricting framework choice.
What enterprise integrations and connectors are available?
The Agents API provides connectors for enterprise systems such as Salesforce, and supports integration with internal APIs across your organization. Agents can access knowledge bases, resolve tickets through automated workflows, and connect to cloud providers like AWS and Azure. On-premise deployment options are available for organizations with strict data residency requirements.
Which cloud providers are supported for multi-cloud deployment?
The Agents API supports deployment across major cloud providers including AWS, Azure, and GCP (Google Cloud Platform), as well as your self-deployed and on-premise Kubernetes environments. You can deploy agents to any provider or cluster without limiting yourself to a single cloud provider. The platform allows operating agents across multiple environments while maintaining a unified control plane. Pre-built integrations and retrieval capabilities work consistently regardless of which cloud infrastructure you choose.
Frameworks & Compatibility
Which AI agent frameworks and platforms does the Agents API support?
The Agents API supports all major platforms and frameworks including LangChain, CrewAI, AutoGen, Agno, Strands (AWS), Google ADK, and OpenAI Agents SDK. This interoperability means teams can use their best framework choice while maintaining a unified API layer. The framework-agnostic design enables multi-agent orchestration across different implementations.
Can I migrate agents from one framework to another?
Yes. The Agents API provides a standardized invocation contract that works across similar frameworks. This means you can start with one platform and migrate agents to a different runtime without changing your integration code. Supporting multiple frameworks enables gradual adoption and reduces vendor lock-in.
How does the Agents API compare to alternatives for deploying AI agents?
In comparison to building custom infrastructure or using point solutions, the Agents API handles the complexity of running and deploying autonomous agents at scale. Key differences include native multi-framework support, Kubernetes-native deployment, and a unified management layer. The platform works well with your existing security stack and ecosystem, avoiding the need to maintain separate infrastructure for each framework.
What features should I consider when choosing an AI agent platform?
Key considerations include framework support (e.g. LangChain, CrewAI), deployment flexibility, security features, and scalable infrastructure. Consider whether the platform provides data residency options for compliance, vendor-neutral tooling that avoids lock-in, and integration with your existing corporate infrastructure. Business teams should evaluate how well the platform automates common workflows instead of requiring custom development.
What workflow automation capabilities does the Agents API offer beyond general automation tools?
Unlike general workflow automation tools, the Agents API is purpose-built for autonomous AI agents and generative AI workloads. It provides APIs specifically designed for agentic patterns, supports multi-agent orchestration, and handles the unique requirements of LLM-based applications. The platform helps companies build intelligent automation that goes beyond rule-based workflows, compatible with existing RPA investments.
How do I move from prototype to production with the Agents API?
The platform is designed to complement your development workflow from prototype to production-ready deployment. Tips for productionizing include using the APIs for programmatic agent management, leveraging built-in observability, and configuring runtimes for your specific workload. The enterprise-ready infrastructure means you can scale without rebuilding, and examples in the documentation show strategies for common deployment patterns.
Enterprise & Production
What are the deployment options for production workloads?
The Agents API offers flexible deployment options for production environments. Run agents serverless in our cloud, deploy to your own Kubernetes clusters (K8s), or use a multi-cloud approach. For production deployment at scale, you can choose between managed infrastructure or self-hosted options depending on your security and compliance requirements.
Is the Agents API suitable for enterprise-grade applications?
Yes. The platform provides enterprise-grade security with managed authentication, PII masking, and audit trails. The integration with existing enterprise infrastructure, support for private Kubernetes deployment, and comprehensive monitoring make it ideal for production enterprise applications. These solutions help departments across your organization adopt AI agents securely.
What are the best practices for secure deployment?
Best practices include deploying directly to your Kubernetes-native infrastructure, using the secure API authentication, and enabling audit trails for compliance. For fully self-hosted deployments, the platform integrates with your existing security stack. You can reuse existing Kubernetes configurations and handle agent deployment through standard CI/CD pipelines. Technical teams appreciate the automation capabilities for managing agents across multiple environments.
Is open source or self-hosting supported?
Yes. The platform supports self-hosting and deploys to your private infrastructure. For enterprises that require open source components or full control, the Agents API works with your existing infrastructure. Self-hosting options include deploying as containers in your cloud-native environment with scaling managed by your infrastructure team.
Can the Agents API support customer service and IT service desk automation?
Yes. The Agents API is ideal for building AI agents that handle customer support automation, IT service desk operations, and technical support workflows. Agents can access company docs and documentation, resolve tickets through automated workflows, and provide intelligent responses. The platform supports building agents that handle automated ticket resolution for employee support, integrating with existing helpdesk and ticketing systems while maintaining quality through observability and audit trails.
Can the Agents API automate helpdesk and business workflows?
Yes. The platform is well-suited for automating helpdesk operations, business process automation, and internal workflow automation. You can build agents that automate ticket routing, provide intelligent responses, and integrate with existing software systems. The scalable architecture handles varying loads while providing observability into what agents are doing in production. Large companies and organizations across industries use the platform for employee support, code review automation, etc.
Frequently Asked Questions
API & Integration
How does the Agents API integrate with existing applications?
The Agents API provides a standard REST endpoint that you can integrate into any application. It supports multiple deployment options including cloud-hosted and self-hosted on your own Kubernetes clusters. The unified integration layer means you can connect agents to customer support tickets, enterprise search, or any custom workflow with minimal code changes.
What monitoring and tracing capabilities are available?
The Agents API includes built-in observability with monitoring and tracing for production workloads. You can track agent execution, view intermediate steps through SSE streaming, and access comprehensive audit logs for enterprise-grade compliance.
What backend services does the Agents API provide?
The Agents API can function as a BaaS (Backend-as-a-Service) for AI agents, handling infrastructure concerns so developers can focus on agent logic. Services include managed scaling, event triggers, observability, and deployment pipelines. The platform integrates with DevOps and MLOps workflows, enabling teams to productionize agents and LLM models using familiar CI/CD practices.
How does the Agents API serve as a control plane for AI agents?
The Agents API acts as a unified control plane for managing AI agents across your organization. Developers can build agents using their preferred frameworks while the platform provides centralized management, scaling, and observability. This enables internal teams and platform architects to maintain governance over all agent deployments without restricting framework choice.
What enterprise integrations and connectors are available?
The Agents API provides connectors for enterprise systems such as Salesforce, and supports integration with internal APIs across your organization. Agents can access knowledge bases, resolve tickets through automated workflows, and connect to cloud providers like AWS and Azure. On-premise deployment options are available for organizations with strict data residency requirements.
Which cloud providers are supported for multi-cloud deployment?
The Agents API supports deployment across major cloud providers including AWS, Azure, and GCP (Google Cloud Platform), as well as your self-deployed and on-premise Kubernetes environments. You can deploy agents to any provider or cluster without limiting yourself to a single cloud provider. The platform allows operating agents across multiple environments while maintaining a unified control plane. Pre-built integrations and retrieval capabilities work consistently regardless of which cloud infrastructure you choose.
Frameworks & Compatibility
Which AI agent frameworks and platforms does the Agents API support?
The Agents API supports all major platforms and frameworks including LangChain, CrewAI, AutoGen, Agno, Strands (AWS), Google ADK, and OpenAI Agents SDK. This interoperability means teams can use their best framework choice while maintaining a unified API layer. The framework-agnostic design enables multi-agent orchestration across different implementations.
Can I migrate agents from one framework to another?
Yes. The Agents API provides a standardized invocation contract that works across similar frameworks. This means you can start with one platform and migrate agents to a different runtime without changing your integration code. Supporting multiple frameworks enables gradual adoption and reduces vendor lock-in.
How does the Agents API compare to alternatives for deploying AI agents?
In comparison to building custom infrastructure or using point solutions, the Agents API handles the complexity of running and deploying autonomous agents at scale. Key differences include native multi-framework support, Kubernetes-native deployment, and a unified management layer. The platform works well with your existing security stack and ecosystem, avoiding the need to maintain separate infrastructure for each framework.
What features should I consider when choosing an AI agent platform?
Key considerations include framework support (e.g. LangChain, CrewAI), deployment flexibility, security features, and scalable infrastructure. Consider whether the platform provides data residency options for compliance, vendor-neutral tooling that avoids lock-in, and integration with your existing corporate infrastructure. Business teams should evaluate how well the platform automates common workflows instead of requiring custom development.
What workflow automation capabilities does the Agents API offer beyond general automation tools?
Unlike general workflow automation tools, the Agents API is purpose-built for autonomous AI agents and generative AI workloads. It provides APIs specifically designed for agentic patterns, supports multi-agent orchestration, and handles the unique requirements of LLM-based applications. The platform helps companies build intelligent automation that goes beyond rule-based workflows, compatible with existing RPA investments.
How do I move from prototype to production with the Agents API?
The platform is designed to complement your development workflow from prototype to production-ready deployment. Tips for productionizing include using the APIs for programmatic agent management, leveraging built-in observability, and configuring runtimes for your specific workload. The enterprise-ready infrastructure means you can scale without rebuilding, and examples in the documentation show strategies for common deployment patterns.
Enterprise & Production
What are the deployment options for production workloads?
The Agents API offers flexible deployment options for production environments. Run agents serverless in our cloud, deploy to your own Kubernetes clusters (K8s), or use a multi-cloud approach. For production deployment at scale, you can choose between managed infrastructure or self-hosted options depending on your security and compliance requirements.
Is the Agents API suitable for enterprise-grade applications?
Yes. The platform provides enterprise-grade security with managed authentication, PII masking, and audit trails. The integration with existing enterprise infrastructure, support for private Kubernetes deployment, and comprehensive monitoring make it ideal for production enterprise applications. These solutions help departments across your organization adopt AI agents securely.
What are the best practices for secure deployment?
Best practices include deploying directly to your Kubernetes-native infrastructure, using the secure API authentication, and enabling audit trails for compliance. For fully self-hosted deployments, the platform integrates with your existing security stack. You can reuse existing Kubernetes configurations and handle agent deployment through standard CI/CD pipelines. Technical teams appreciate the automation capabilities for managing agents across multiple environments.
Is open source or self-hosting supported?
Yes. The platform supports self-hosting and deploys to your private infrastructure. For enterprises that require open source components or full control, the Agents API works with your existing infrastructure. Self-hosting options include deploying as containers in your cloud-native environment with scaling managed by your infrastructure team.
Can the Agents API support customer service and IT service desk automation?
Yes. The Agents API is ideal for building AI agents that handle customer support automation, IT service desk operations, and technical support workflows. Agents can access company docs and documentation, resolve tickets through automated workflows, and provide intelligent responses. The platform supports building agents that handle automated ticket resolution for employee support, integrating with existing helpdesk and ticketing systems while maintaining quality through observability and audit trails.
Can the Agents API automate helpdesk and business workflows?
Yes. The platform is well-suited for automating helpdesk operations, business process automation, and internal workflow automation. You can build agents that automate ticket routing, provide intelligent responses, and integrate with existing software systems. The scalable architecture handles varying loads while providing observability into what agents are doing in production. Large companies and organizations across industries use the platform for employee support, code review automation, etc.
Frequently Asked Questions
API & Integration
How does the Agents API integrate with existing applications?
The Agents API provides a standard REST endpoint that you can integrate into any application. It supports multiple deployment options including cloud-hosted and self-hosted on your own Kubernetes clusters. The unified integration layer means you can connect agents to customer support tickets, enterprise search, or any custom workflow with minimal code changes.
What monitoring and tracing capabilities are available?
The Agents API includes built-in observability with monitoring and tracing for production workloads. You can track agent execution, view intermediate steps through SSE streaming, and access comprehensive audit logs for enterprise-grade compliance.
What backend services does the Agents API provide?
The Agents API can function as a BaaS (Backend-as-a-Service) for AI agents, handling infrastructure concerns so developers can focus on agent logic. Services include managed scaling, event triggers, observability, and deployment pipelines. The platform integrates with DevOps and MLOps workflows, enabling teams to productionize agents and LLM models using familiar CI/CD practices.
How does the Agents API serve as a control plane for AI agents?
The Agents API acts as a unified control plane for managing AI agents across your organization. Developers can build agents using their preferred frameworks while the platform provides centralized management, scaling, and observability. This enables internal teams and platform architects to maintain governance over all agent deployments without restricting framework choice.
What enterprise integrations and connectors are available?
The Agents API provides connectors for enterprise systems such as Salesforce, and supports integration with internal APIs across your organization. Agents can access knowledge bases, resolve tickets through automated workflows, and connect to cloud providers like AWS and Azure. On-premise deployment options are available for organizations with strict data residency requirements.
Which cloud providers are supported for multi-cloud deployment?
The Agents API supports deployment across major cloud providers including AWS, Azure, and GCP (Google Cloud Platform), as well as your self-deployed and on-premise Kubernetes environments. You can deploy agents to any provider or cluster without limiting yourself to a single cloud provider. The platform allows operating agents across multiple environments while maintaining a unified control plane. Pre-built integrations and retrieval capabilities work consistently regardless of which cloud infrastructure you choose.
Frameworks & Compatibility
Which AI agent frameworks and platforms does the Agents API support?
The Agents API supports all major platforms and frameworks including LangChain, CrewAI, AutoGen, Agno, Strands (AWS), Google ADK, and OpenAI Agents SDK. This interoperability means teams can use their best framework choice while maintaining a unified API layer. The framework-agnostic design enables multi-agent orchestration across different implementations.
Can I migrate agents from one framework to another?
Yes. The Agents API provides a standardized invocation contract that works across similar frameworks. This means you can start with one platform and migrate agents to a different runtime without changing your integration code. Supporting multiple frameworks enables gradual adoption and reduces vendor lock-in.
How does the Agents API compare to alternatives for deploying AI agents?
In comparison to building custom infrastructure or using point solutions, the Agents API handles the complexity of running and deploying autonomous agents at scale. Key differences include native multi-framework support, Kubernetes-native deployment, and a unified management layer. The platform works well with your existing security stack and ecosystem, avoiding the need to maintain separate infrastructure for each framework.
What features should I consider when choosing an AI agent platform?
Key considerations include framework support (e.g. LangChain, CrewAI), deployment flexibility, security features, and scalable infrastructure. Consider whether the platform provides data residency options for compliance, vendor-neutral tooling that avoids lock-in, and integration with your existing corporate infrastructure. Business teams should evaluate how well the platform automates common workflows instead of requiring custom development.
What workflow automation capabilities does the Agents API offer beyond general automation tools?
Unlike general workflow automation tools, the Agents API is purpose-built for autonomous AI agents and generative AI workloads. It provides APIs specifically designed for agentic patterns, supports multi-agent orchestration, and handles the unique requirements of LLM-based applications. The platform helps companies build intelligent automation that goes beyond rule-based workflows, compatible with existing RPA investments.
How do I move from prototype to production with the Agents API?
The platform is designed to complement your development workflow from prototype to production-ready deployment. Tips for productionizing include using the APIs for programmatic agent management, leveraging built-in observability, and configuring runtimes for your specific workload. The enterprise-ready infrastructure means you can scale without rebuilding, and examples in the documentation show strategies for common deployment patterns.
Enterprise & Production
What are the deployment options for production workloads?
The Agents API offers flexible deployment options for production environments. Run agents serverless in our cloud, deploy to your own Kubernetes clusters (K8s), or use a multi-cloud approach. For production deployment at scale, you can choose between managed infrastructure or self-hosted options depending on your security and compliance requirements.
Is the Agents API suitable for enterprise-grade applications?
Yes. The platform provides enterprise-grade security with managed authentication, PII masking, and audit trails. The integration with existing enterprise infrastructure, support for private Kubernetes deployment, and comprehensive monitoring make it ideal for production enterprise applications. These solutions help departments across your organization adopt AI agents securely.
What are the best practices for secure deployment?
Best practices include deploying directly to your Kubernetes-native infrastructure, using the secure API authentication, and enabling audit trails for compliance. For fully self-hosted deployments, the platform integrates with your existing security stack. You can reuse existing Kubernetes configurations and handle agent deployment through standard CI/CD pipelines. Technical teams appreciate the automation capabilities for managing agents across multiple environments.
Is open source or self-hosting supported?
Yes. The platform supports self-hosting and deploys to your private infrastructure. For enterprises that require open source components or full control, the Agents API works with your existing infrastructure. Self-hosting options include deploying as containers in your cloud-native environment with scaling managed by your infrastructure team.
Can the Agents API support customer service and IT service desk automation?
Yes. The Agents API is ideal for building AI agents that handle customer support automation, IT service desk operations, and technical support workflows. Agents can access company docs and documentation, resolve tickets through automated workflows, and provide intelligent responses. The platform supports building agents that handle automated ticket resolution for employee support, integrating with existing helpdesk and ticketing systems while maintaining quality through observability and audit trails.
Can the Agents API automate helpdesk and business workflows?
Yes. The platform is well-suited for automating helpdesk operations, business process automation, and internal workflow automation. You can build agents that automate ticket routing, provide intelligent responses, and integrate with existing software systems. The scalable architecture handles varying loads while providing observability into what agents are doing in production. Large companies and organizations across industries use the platform for employee support, code review automation, etc.
The AI Agent Platform
for Enterprise Teams
Build with any framework. Deploy on any cloud. Orchestration, security, and observability built in.
The AI Agent Platform
for Enterprise Teams
Everything you need to build, deploy,
and scale your AI agents
The AI Agent Platform for Enterprise Teams
Build with any framework. Deploy on any cloud. Orchestration, security, and observability built in.
