Build autonomous AI agents that execute multi-step workflows, integrate with your tools, and automate complex business processes. From single-purpose agents to orchestrated multi-agent systems.

What you get:

Agent architecture design (single or multi-agent)

Tool integration (APIs, databases, internal systems)

Workflow orchestration with state management

Error handling and recovery mechanisms

Observability and monitoring (traces, logs, metrics)

Production deployment and scaling

Documentation and runbooks

Use cases I've built:

OptX ERP Agent: Agent-based platform that automates Canias ERP operations, with agent orchestration for workflow execution, monitoring, and reporting

Recram Video Agent: Cloud-native agent-based architecture for video intelligence processing on Kubernetes

AI orchestration layers for custom enterprise workflows

Why me: I've built production agentic systems with subscription management, usage limits, multi-tenant architecture, and message queue orchestration. Not just demos, real systems handling enterprise workloads.

Tech stack: Node.js, TypeScript, Python, Message Queues (Redis, RabbitMQ), PostgreSQL, Docker, Kubernetes, gRPC microservices.