Multi-LLM Ensemble with Supervisor Agent Pattern

[myui]

Overview

An architecture that combines multiple LLMs (OpenAI, Anthropic, Google, Meta, and in-house open-weight models — often 15+ models), where generated outputs are validated by a Supervisor Agent (a separate model acting as a verifier).

Architecture

1. Worker Layer

   • Multiple LLMs generate outputs in parallel or selectively
   • Each model is leveraged for its strengths (reasoning, coding, multilingual, etc.)

2. Supervisor Layer

   • Validates, compares, and reranks outputs
   • Performs hallucination detection, consistency checks, and policy validation
   • Optionally triggers regeneration or refinement loops

Characteristics

• Higher reliability and output quality than single-model systems
• Reduced vendor lock-in through model diversity
• Increased cost and latency due to multi-model execution

Use Cases

• High-reliability agents (customer support, finance, legal)
• Code generation with verification
• Stabilizing long-form reasoning tasks

Related Patterns

• Self-Consistency
• Debate / Multi-agent critique
• Reflection / ReAct with verifier

Notes

This pattern can be seen as a combination of:

• Mixture of Experts (MoE)
• Ensemble methods with a critic/verifier model

In Graflow, this maps naturally to:

• Task Graph with fan-out to multiple workers
• Aggregation + Supervisor node for validation