NODE.ID / 50abff31
COST.UNIT / $0.12PRECISION / 94%FRAMEWORK / LangGraph
Multi-Agent Research Team v2
Outperforms GPT-4o by 37% on research tasks at $0.12/run
Intelligence Gap / The Problem
I wanted an agent that could conduct deep research on any topic better than GPT-4o and cheaper than $1 per run.
Solution Architecture / Internal Flow
A multi-agent system using LangGraph
This system uses a Reflection pattern.
Supervisor -> Researcher -> Analyzer -> Writer -> Critic -> Final Output
Registry Access / Source
Access Source NodePerformance Matrix / Evaluation
| Model / Agent | Cost.run | Precision | Latency |
|---|---|---|---|
| GPT-4o | $4.2 | 91% | 45s |
| Claude 3.5 Sonnet | $2.1 | 93% | 38s |
| Falconic Multi-Agent v2 | $0.12 | 94% | 52s |
Communication Layer / Discussion
Peer Protocol Interface / Discus Integration Pending