The Problem Agent Kernel Solves
Building production AI agents today involves solving many hard problems that have nothing to do with the actual agent intelligence.
Every Request, Fully Orchestrated
Agent Kernel wraps your agent logic in a structured, inspectable execution pipeline — from user message to validated response.
Core Capabilities
Everything you need to build, run, and scale production AI agents — without building platform code.
Six Core Abstractions
Agent, Runner, Session, Module, Runtime, and Tools — a unified API across all frameworks. Build once, run on any supported framework.
- Unified Python API
- Framework adapters for 4 SDKs
- Portable tool functions via ToolBuilder
- Framework-agnostic hooks
Framework-Agnostic Runtime
OpenAI Agents, LangGraph, CrewAI, and Google ADK — run them all simultaneously in one runtime. Switch frameworks by changing 2 import lines.
- OpenAI Agents SDK
- LangGraph
- CrewAI
- Google ADK
Execution Hooks
Pre and post-execution hooks give you surgical control over every agent request — for any framework.
- Pre-hooks: guardrails, RAG, auth, validation
- Post-hooks: moderation, disclaimers, analytics
- Hook chaining and composition
- Early termination with custom responses
Smart Memory Management
Volatile and non-volatile caching with identical APIs but different lifecycles. Swap backends with just environment variables.
- Volatile: request-scoped, auto-clears
- Non-volatile: session-persistent
- Backends: In-memory, Redis, DynamoDB, Cosmos DB
- Clean prompts, reduced token usage
Multi-Cloud Deployment
One agent codebase deploys to AWS and Azure with full Terraform modules. No vendor lock-in, ever.
- AWS Lambda (Serverless)
- AWS ECS/Fargate (Containerized)
- Azure Functions (Serverless)
- Azure Container Apps (Containerized)
Fault Tolerance
Production-grade resilience with multi-AZ deployments, auto-recovery, health monitoring, and rolling deployments.
- Multi-AZ for high availability
- Automatic failure recovery
- Health monitoring
- Zero-downtime deployments
Observability
Full visibility into agent execution, LLM calls, and tool invocations. One config line to enable.
- LangFuse integration
- OpenLLMetry (OpenTelemetry-based)
- Multi-level verbosity
- Cost and latency tracking
Content Safety & Guardrails
Input and output guardrails that protect users and ensure compliance. Plugs in via execution hooks.
- PII detection and redaction
- Jailbreak prevention
- Content moderation
- Off-topic filtering
MCP & A2A Protocols
Expose agents as MCP tools or enable agent-to-agent communication via A2A protocol.
- MCP Server mode
- A2A Server mode
- Cross-agent coordination
- Protocol-future-proofed
One Runtime. Any Framework.
Use the best framework for each job — and run them all together in a single deployment.
OpenAI Agents SDK
Official OpenAI agents framework with full support for tools, handoffs, and streaming.
Learn more →LangGraph
Graph-based agent orchestration for complex stateful multi-actor applications.
Learn more →Google ADK
Google's Agent Development Kit for advanced agent capabilities and Gemini integration.
Learn more →CrewAI
Role-based multi-agent framework for orchestrating collaborative AI workflows.
Learn more →Multi-Framework
Run agents from multiple frameworks simultaneously in a single runtime — no glue code required.
Learn more →Smart Memory Management
Two cache types with identical APIs, different lifecycles. Swap backends with environment variables — no code changes.
Volatile Cache
Request-scoped temporary storage. Auto-clears after each request. Keeps prompts clean and reduces token usage.
- RAG search results
- Uploaded file content
- Temporary calculations
- Request-scoped flags
Non-Volatile Cache
Session-persistent storage that survives across multiple requests. Share data between hooks and tools.
- User preferences
- Session metadata
- Extracted entities
- Persistent configurations
Redis Backend
High-performance distributed memory for production AWS and Azure workloads.
- Production deployments
- Multi-process apps
- Distributed systems
- Session persistence
DynamoDB / Cosmos DB
Serverless, auto-scaling NoSQL for AWS Lambda and Azure Functions with configurable TTL.
- Serverless deployments
- Auto-scaling apps
- Pay-per-use pricing
- Cloud-native infrastructure
Testing Framework
Test your agents like any other code. CLI testing for development, automated suites for CI/CD. Three comparison modes for every use case.
CLI Testing
Interactive sessions for rapid development iteration and multi-agent testing.
- Interactive chat sessions
- Real-time feedback
- Persistent CLI sessions
- Multi-agent support
Automated Tests
pytest-integrated test suites that run in CI/CD with session-scoped fixtures.
- pytest integration
- Session-scoped fixtures
- Ordered test execution
- CI/CD ready
Deploy Anywhere
From local CLI to global multi-cloud production — the same agent code runs everywhere.
Local Development
CLI testing and REST API server for local iteration.
- CLI interactive sessions
- Automated test scenarios
- No cloud dependencies
- Fast iteration
AWS Serverless
Lambda-based execution for variable, cost-efficient workloads.
- Lambda execution
- Auto-scaling
- Pay-per-use
- DynamoDB session storage
AWS Containerized
ECS/Fargate for consistent, predictable production performance.
- ECS/Fargate
- Multi-AZ
- Predictable performance
- Redis session storage
Azure Serverless
Azure Functions with KEDA-based scaling and Cosmos DB.
- Azure Functions
- KEDA auto-scaling
- Cosmos DB storage
- Pay-per-use
Azure Containerized
Container Apps for multi-zone, high-availability deployments.
- Container Apps
- Multi-zone HA
- Built-in scaling
- Redis session storage
On-Premise / Docker
Full control with Docker and REST API for on-premise deployments.
- Docker support
- REST API server
- Custom infrastructure
- Full control
Infrastructure as Code — Multi-Cloud
Official Terraform modules for AWS and Azure. Production-ready with best practices baked in.
Observability & Traceability
Full visibility into every agent action, LLM call, and tool invocation — with one config line.
Multi-Level Tracing
Track every decision your agents make at the granularity you choose.
- Agent action tracking
- LLM call monitoring with cost estimation
- Tool invocation logs
- Multi-agent collaboration traces
- Performance metrics and latency
LangFuse
Comprehensive LLM observability, analytics, and prompt management platform.
OpenLLMetry (Traceloop)
OpenTelemetry-based observability for LLM applications. Works with any OTel backend.
Content Safety & Guardrails
Validate inputs before agents see them and outputs before users do. Works with any Agent Kernel framework via execution hooks.
Multi-Layer Protection
Validate content at both input and output stages with pluggable providers.
- Input validation before agent processing
- Output validation before delivery
- PII detection and redaction (30+ entity types)
- Jailbreak and prompt attack detection
- Topic blocking and keyword filtering
- Contextual grounding checks
OpenAI Guardrails
Flexible LLM-based content validation with custom rules and policies.
AWS Bedrock Guardrails
Enterprise-grade content filtering with 30+ PII types and contextual grounding checks.
Ready to Build Your AI Agents?
Free, open-source, Apache 2.0. Whether you're an AI startup, an established software company, or a domain expert — Agent Kernel has a path for you.