Delphi | Multi-Agent Orchestration

Multi-Agent Orchestration

One agent is a tool. A team of agents is a workforce. We build the orchestration layer that turns individual AI agents into coordinated enterprise systems — where agents plan together, delegate to each other, and execute complex workflows that no single agent could handle alone.

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Multi-Agent Orchestration

CHALLENGES

Single Agent Limitations

Individual AI agents handle narrow tasks well but cannot manage multi-step workflows that require different capabilities, tools, and decision points.

No Coordination Between AI Systems

Organizations with multiple AI tools have no layer to coordinate them — each operates independently, unable to share context or collaborate on complex tasks.

Agent Reliability at Scale

As agent complexity grows, so does failure risk. Without robust orchestration, testing, and observability frameworks, multi-agent systems become unpredictable in production.

Agent-to-Agent Coordination

Orchestration layers that enable agents to communicate, delegate, and collaborate — using Agno, Semantic Kernel, and Microsoft Agent Framework.

Team Hierarchies & Dynamic Routing

Supervisor-agent architectures where orchestrator agents delegate to specialist agents based on task type, context, and capability.

AG-UI (Agentic GUI) Capability

Agent interfaces that interact with both APIs and user interfaces simultaneously — enabling agents to operate within existing digital platforms and workflows

MCP (Model Context Protocol) Integration

Agents connected to enterprise systems via MCP — giving them structured access to tools, data, and actions across your technology landscape.

Need for Services

Proven Framework Stack

Agno, Semantic Kernel, AutoGen, and Microsoft Agent Framework — we build on the frameworks that enterprise AI teams trust, not proprietary black boxes.

AG-UI Capability

Very few firms can build agents that interact with both APIs and user interfaces. Our AG-UI capability enables agents to operate within your existing digital surfaces.

Production-Hardened Delivery

Our orchestration implementations are tested for behavioral permutations, prompt drift, and edge case handling — not just happy-path scenarios.

Observability Built In

Every multi-agent system we deploy is instrumented for observability — agent trace logging, decision auditing, and performance monitoring.

Factory-Scalable Architecture

Multi-agent systems built to our orchestration standards are compatible with our Agent Factory delivery model — scale from 5 coordinated agents to 50 without architectural rework.

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