AI Workflow Automation · Orchestration
When one agent can't hold the job, orchestrate several that can.
Design then build a multi-agent system: specialized agents orchestrated by a lead over a shared tool and MCP layer, with isolated context, condensed hand-backs, tracing, and staged deploys, so several agents run as one reliable production system.
The package
Agentic Orchestration
Some work is too broad or too parallel for a single agent to hold without losing the thread. This package orchestrates specialized agents into one system, designed deliberately so it stays reliable as it scales. Buy the design, the build, or both as one program.
- A multi-agent blueprint: topology, roles, delegation contracts, and an evaluation plan
- An orchestration layer plus a shared tool and MCP layer that scales without context blowup
- Agent-to-agent execution with isolated context and condensed hand-backs
- Tracing, checkpoints, and staged deploys to manage emergent behavior
What's inside
Projects in this package
Agentic System Design
The multi-agent blueprint before the build: a topology decision (manager vs decentralized), agent roles and delegation contracts, an evaluation plan, and a context-isolation design.
Explore
Agentic System Build
Build and orchestrate the system: a lead agent that decomposes and delegates, a shared tool and MCP layer with progressive disclosure, isolated subagent context, and tracing, checkpoints, and staged deploys.
ExploreOne system, three layers
Make the system production-trustworthy
A multi-agent system in a regulated setting needs the trust layer. AI Governance & Evaluation makes it measurable, auditable, and defensible.