Practice

AI engineering and multi-agent systems

I design AI systems that bring together specialized agents, language models, memory and tools. I develop their orchestration and their capabilities for analysis, automation and interaction, while exploring prediction and decision support through machine learning.

Scope

Applied capabilities

  • Distributed multi-agent orchestration, capability-based routing and tool-enabled Python workflows
  • Local LLM routing, GGUF operations, and resource-aware model loading
  • Graph and vector memory, event buses, and real-time interaction
  • Predictive experimentation, forecasting and simulated decision support
  • Voice and multimodal interaction: streaming speech, vision and document processing
  • Observability, circuit breakers, dead-letter queues, offline buffers and recovery
  • Applications include commerce and customer support: Python services connected to business APIs, with operator review and escalation in support workflows
  • Pilot design, controls, evidence, and governance for AI adoption