See what you're missing before you commit.

Multiple AI models debate your question in structured blind rounds. Instead of one confident answer, you get a map of what's solid, what's contested, and what only you can decide.

Backed by MIT/DeepMind research
Cross-company AI neutrality
Full audit trail
EU AI Act ready
Model AModel BModel CConsensus EngineStructured Output
Blind
Generate
Exchange
Debate
Refine
Output

One AI. One opinion. Zero accountability.

The Confidence Trap

Single AI models hallucinate with full confidence. You can't tell a solid answer from a fabrication.

The Brand Bias

You trust Claude because it's Anthropic, or GPT because it's OpenAI. Brand deference lets weak reasoning hide behind a logo.

The Black Box

You get an answer. You don't get to see how it was reached, what was considered, or what was missed.

The Consensus Debate Protocol

A 6-phase pipeline that produces information no single model can generate.

Phase 0

Input Analysis

User submits any type of thinking — a question, proposal, prediction, belief, or idea. The system classifies the input type and adapts the entire downstream pipeline.

  • Factual, normative, proposal, prediction, brainstorm, evaluation, belief, or definition
  • Honest disclaimer for pure fact retrieval: 'Debate shows smaller gains on pure fact retrieval'
Phase 0.5

Optional Grounding

For evidence-heavy inputs, the system retrieves verified external sources and anchors all models to the same evidence base.

  • Web search or uploaded documents
  • Prevents debates from becoming contests of memorized training data
Phase 1Key Phase

Blind Round

Three AI models answer independently and simultaneously. No model sees any other's response. Identities are anonymized — Model A, Model B, Model C, never brand names.

  • Convergence independence — claims multiple models arrived at independently
  • This is the strongest trust signal in the entire system
Phase 2

Deliberation Rounds

Models receive anonymized responses from others. They must challenge, support, or refine specific claims — not argue in prose.

  • If a model changes position, it must state what changed its mind
  • Vagueness penalty downweights claims that get broader to dodge disagreement
  • Minority corrections — when a lone dissenter catches something the majority missed
Phase 3

Consensus Check

An adjudicator evaluates the debate. The consensus score is decomposed into 4 visible components — not a black box number.

  • Stance Alignment (0–40)
  • Empirical Claim Overlap (0–25)
  • Framework Agreement (0–20)
  • Confidence Convergence (0–15)
Phase 4Key Phase

Synthesis: The Four-Part Output

The synthesizer compiles everything into four distinct sections — this is the product.

The Four-Part Output

Strong Ground

Claims all models converged on. Blind agreements at the top, later adoptions below. Each claim tagged with confidence spread and evidence cited.

Here's what you can rely on.

Fault Lines

Precise points of disagreement, expressed as conditionals. Tagged with which models are on which side, whether empirical or normative.

Here's where the uncertainty lives.

Blind Spots

Claims only one model raised but others validated after seeing them. Tagged with origin, validation status, and significance.

Here's what you would have missed asking just one AI.

Your Call

Decision points where AI knowledge runs out entirely. Classified as: values decisions, risk appetite, priorities, or genuine unknowables.

Here's where you bring your own judgment.

Disagreement is the product.

Existing multi-model systems like FusionFactory fuse multiple AIs to produce a single optimized answer — they merge disagreement away. We do the opposite.

We preserve the disagreement structure because compliance officers and legal analysts need to see where models diverge, not just get a blended result that hides the fault lines.

ICLR 2025 found that multi-agent debate doesn't reliably beat a single strong model on accuracy benchmarks. We don't fight that finding — we built around it.

Our product's value isn't a more accurate answer. It's information that doesn't exist without multiple independent models confronting each other: convergence independence, fault lines, blind spots, minority corrections.

Single AIAI FusionCDP
OutputOne confident answerOne optimized answerStructured uncertainty map
DisagreementHiddenMerged awayPreserved as the product
Audit trailFull reasoning transparency
Blind spotsInvisibleInvisibleSurfaced and tagged
Trust signal"Trust the brand""Trust the blend""See the evidence"

Built for decisions with consequences.

Compliance Officers

Before: synthesize regulatory guidance across 3 AI tools manually.

After: structured analysis with audit trail in minutes. EU AI Act ready.

Legal Analysts

Before: ask one AI and hope.

After: see exactly where legal reasoning diverges and which assumptions drive each conclusion.

Research & Strategy Teams

Before: get one confident prediction.

After: see the conditions under which different outcomes follow, and what would need to be true for each.

Before, analysts spent 4 hours synthesizing regulatory guidance across tools. Now the debate map produces structured analysis in 12 minutes — audit trail included.

— Enterprise pilot, Financial Services

Start free. Scale when you're ready.

Free

$0/month

Start exploring structured debate

Join Free
  • 5 debates/day (150/month)
  • 2 rounds maximum
  • Models: Gemini Flash + Groq/Llama + Mistral
  • Algorithmic consensus scoring
  • Simplified debate map output
  • Watermarked output
  • No audit export
Most Popular

Pro

$29/month

For professionals who need clarity

Start Pro
  • 100 debates/month included
  • $0.35/debate overage
  • Up to 4 rounds
  • Models: Claude Sonnet + GPT-4o + Gemini Pro
  • 2-model adjudicator committee
  • Full four-part output
  • Full debate map with drill-down
  • JSON audit trail export
  • No watermark
  • 2 API keys for MCP integration

Enterprise

Custom

Tailored for your organization

Contact Sales
  • Unlimited debates
  • Up to 10 rounds
  • Configurable models (BYOK option)
  • On-premise or private cloud deployment
  • Ephemeral mode (zero data stored)
  • EU AI Act, SOC2, HIPAA-ready
  • Full audit trail on client infrastructure
  • Dedicated support + SLA

All payments processed on web. No app store markup. Same model as ChatGPT and Perplexity.

First Public Integration Tool

Bring structured debate into any AI workflow.

The Consensus Debate Protocol MCP server is the first public tool — add multi-model deliberation to Claude Code, Cursor, Windsurf, or any MCP-compatible client.

MCP (Model Context Protocol) lets AI assistants call external tools. Our MCP server wraps the full debate engine into two simple tools. Start a debate from your terminal, IDE, or Claude Desktop — get back a structured uncertainty map without leaving your workflow.

Use debate() when a question has significant consequences and needs verification beyond a single AI answer. The system runs the full protocol — blind rounds, deliberation, consensus checking — and returns the four-part output plus raw structured data.

MCP Client Compatibility

ClientMCP SupportExperience
Claude Code (terminal)
Full
Round-by-round progress in terminal
Cursor / Windsurf / Zed
Full
IDE integration
Claude.ai Desktop
Full
Power user workflow
Claude.ai Web
Not yet
Use web app directly
ChatGPT
Not yet
Use web app directly

MCP server launches Month 8. REST API available Month 6 with Python + JS SDKs. Join the waitlist for early access.

debate.ts
// MCP Tool: debate()
// Input
{
"text-primary">question: "Should we migrate our auth system to OAuth 2.1?",
"text-primary">context: "Current system uses session tokens, 50k DAU",
"text-primary">rounds: 3
}
// Output includes both narrative and structured data
{
"text-primary">narrative: "Three models deliberated over 3 rounds...",
"text-primary">consensus_score: 0.74,
"text-primary">consensus_reached: false,
"text-primary">rounds_taken: 3,
"text-primary">strong_ground: ["OAuth 2.1 improves security posture...", ...],
"text-primary">fault_lines: [
{
"text-primary">condition: "If migration budget exceeds $200k",
"text-primary">position_a: "Phased migration recommended",
"text-primary">position_b: "Full cutover more cost-effective",
"text-primary">type: "empirical"
}
],
"text-primary">blind_spots: ["Session token rotation vulnerability..."],
"text-primary">your_call: ["Risk appetite for 2-week auth downtime window"],
"text-primary">round_summaries: [...]
}
status.ts
// MCP Tool: debate_status()
// For async workflows — start debate, do other work, check back
{
"text-primary">debate_id: "dbt_a1b2c3d4"
}
// Returns: { status: "complete", result: { ... } }

Stop trusting. Start verifying.

Run your first debate in 10 seconds. No API keys. No setup.