πΌ Strategy
Executive Decisions
Architecture decision, deployment strategy, resource allocation β bring multiple AI perspectives to the table before committing.
Architecture Module
Powered by Multi-Agent Consensus Protocol Plugin
Collaborative Decision Engine
Your AI team debates before it acts.
Before executing a critical task, agents debate the best approach. This "Mix of Experts" review process significantly reduces errors and hallucinations compared to single-agent execution.
Single AI = single point of failure. One hallucination and your report is wrong, your email goes out wrong, your code ships broken.
Live Demo
Watch Your AI Team Deliberate
Multiple specialized agents debate in real time β then reach a consensus decision.
Multi-Agent Consensus Protocol Β· In Progress
4 agents
π Topic: "Should we launch the new pricing page next week?"
Why It Matters
Single AI vs. Agent Team
The difference between a single agent guessing and a team of experts agreeing.
Without Multi-Agent Consensus Protocol
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One AI answers β ships immediately
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Single point of hallucination
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No record of reasoning
With Multi-Agent Consensus Protocol
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Multiple AIs debate β best answer wins
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Peer review catches errors before execution
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Auto-generated meeting minutes
Use Cases
Built for High-Stakes Decisions
Any decision that matters too much to leave to a single AI.
π Go/No-Go
Product Launches
Risk assessment, go/no-go decisions with evidence from research, engineering, and market analysis agents all in one debate.
π° Audit
Financial Reviews
Multi-agent audit before reports go out. Every number checked, every assumption challenged β automatically.
ποΈ Engineering
Architecture Choices
Tech stack debates with specialized engineering agents. Get consensus before a single line of code is written.
Under the Hood
How the Debate Works
Each agent brings its own expertise. A coordinator orchestrates the discussion, compresses history to keep costs low, and detects consensus β so meetings stay sharp no matter how complex the topic.
1. Topic broadcast Coordinator sends the question to all specialist agents simultaneously 2. Expert responses Each agent contributes from its domain β research, risk, engineering, and more 3. Stance detection AGREE / DISAGREE / NEUTRAL parsed deterministically β no hallucinated consensus 4. Early exit If all agree, the meeting closes immediately and minutes are written 5. Auto minutes Full transcript, summaries, and final verdict saved to Markdown automatically O(1)
Token cost per round
3
Stance types: AGREE / DISAGREE / NEUTRAL
Auto
Early exit on consensus
1 cmd
To start any meeting