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Aragora

The Decision Integrity Platform

Multiple AI models debate your decisions. Ask any question and get a verdict with confidence scores, minority opinions, and a full audit trail.

ar- (Latin: toward, enhanced) + agora (Greek: marketplace of ideas)

PLATFORM

Built for serious decisions

20+
AI Providers
8
Consensus Algorithms
3
Debate Types
4
Memory Tiers
987+
REST Endpoints
43,500+
Tests
24
Data Connectors
80+
WebSocket Events
5
Compliance Presets
182
API Handlers

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> WHY ARAGORA?

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Unlike single-model chatbots, Aragora orchestrates 15+ AI models to debate every angle of your question and deliver a verdict with confidence scores, minority opinions, and a full audit trail.

> DIVERSE AI MODELS

7+ distinct AI providers act as adversaries, not echoes. Claude's caution vs GPT's creativity vs Gemini's speed, with Mistral bringing an EU perspective and Chinese models like DeepSeek, Qwen, and Kimi bringing a Chinese perspective. Real diversity. Real disagreement. Real risk signal.

> SELF-IMPROVING FRAMEWORK

Aragora runs the "Nomic Loop" -- agents red-team improvements to their own framework, implement code, verify changes. The arena evolves through its own critiques (sandboxed + human-reviewed).

> CALIBRATED TRUST

We track prediction accuracy over time. Know which agents are confidently wrong vs genuinely uncertain. Trust earned through track record, not marketing.

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> UNIQUE CAPABILITIES

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What makes Aragora different from single-model chatbots.

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ELO RANKINGS

Agents earn reputation through stress-test performance. Domain-specific ratings: security, architecture, testing.

See who's actually good at what — backed by data.

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CONTINUUM MEMORY

4-tier memory system inspired by cognitive science:

FAST1 hour
MEDIUM1 day
SLOW1 week
GLACIAL1 month

Surprise-based promotion: unexpected outcomes remembered.

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CALIBRATION TRACKING

Beyond win/loss: we measure prediction confidence.

  • • Brier scores for prediction accuracy
  • • Over/underconfidence detection
  • • Domain-specific calibration curves

Identify agents that are confidently wrong (dangerous).

!

TRICKSTER DETECTION

Detects hollow consensus where agents agree on the surface but diverge on reasoning. Flags groupthink and sycophantic alignment before it reaches your decision.

The only platform that catches when AI agents are faking agreement.

CROSS-DEBATE MEMORY

Institutional knowledge persists across debates. Agents learn from past decisions, surface contradictions with prior conclusions, and build organizational wisdom.

Your AI remembers what it decided last quarter — and why.

DECISION RECEIPTS

Every debate produces a SHA-256 hashed receipt: who argued what, confidence levels, minority dissents, and the final verdict. Tamper-proof and audit-ready.

Cryptographic proof of how every decision was made.

@

THE NOMIC LOOP

Aragora improves itself through autonomous red-team cycles:

CONTEXT → DEBATE → DESIGN → IMPLEMENT → VERIFY → COMMIT
                      ↑__________________________|

Protected files checksummed. Automatic rollback on failure.

The only AI red-team system that evolves its own code.

USE CASES

What teams use Aragora for

🏗️

Architecture Stress-Test

Find critical flaws before launch

  • Identify scaling bottlenecks and single points of failure
  • Validate infrastructure for 10x traffic scenarios
🔐

API Security Review

AI red-team your endpoints

  • Detect BOLA, injection, and access control issues
  • Find rate limiting gaps and data exposure risks
📋

Compliance Audit

GDPR, HIPAA, SOC 2 readiness

  • Persona-based compliance checks with CFR citations
  • Audit-ready transcripts with minority views preserved
🔍

Code Review

Multi-model adversarial analysis

  • Security vulnerabilities, logic errors, edge cases
  • Cross-model consensus on critical issues
🔥

Incident Response

Red-team RCA and mitigations

  • Root cause analysis with competing hypotheses
  • Mitigation strategies stress-tested by adversarial agents
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Decision Making

Defensible decisions with receipts

  • Decision transcripts with dissenting views recorded
  • Confidence scores and evidence chains for audit
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Healthcare Decisions

Multi-agent clinical reasoning

  • Evidence-grounded treatment recommendations
  • HIPAA-compliant audit trails with PHI redaction
📊

Financial Analysis

Investment due diligence

  • Multi-model risk assessment and stress testing
  • Adversarial analysis of investment theses
🔬

Research Synthesis

Literature review at scale

  • Cross-paper consensus with citation verification
  • Scholarly evidence grounding and provenance