7 AI Experts. One Document. Zero Blind Spots.
The Agentic Council is the world's first multi-agent document review system. Seven specialized AI experts independently analyze your work, then debate their findings in real-time — catching issues that single-pass detectors miss.
The 7 Experts
Each agent brings a distinct specialty. Together, they leave nothing unchecked.
Dr. Elena Vasquez
Writing Quality Expert
Former Harvard Linguistics Professor
20 years in academic publishing. Analyzes grammar, readability, tone consistency, and style — ensuring your document reads with authority and clarity.
Prof. Marcus Chen
Fact-Checker
Former Reuters Senior Fact-Checker
Former investigative journalist. Cross-references every claim against trusted sources, flags unsupported assertions, and identifies logical fallacies.
Dr. Amara Okafor
Citation Authority
Research Librarian, Oxford Bodleian Libraries
Research librarian with 15 years at Oxford. Evaluates source quality, citation formatting, missing references, and bibliographic completeness.
Prof. Nikolai Petrov
Logic & Structure Expert
Philosophy Chair, ETH Zurich
Philosophy chair specializing in argumentation theory. Maps argument flow, identifies structural gaps, and ensures logical coherence throughout.
Dr. Sarah Kim
AI Detection Expert
AI Research Scientist, Stanford NLP Lab
Stanford NLP researcher focused on machine-generated text. Detects AI-written passages, plagiarism patterns, and content authenticity signals.
Prof. James Whitfield
Subject Matter Expert
Multidisciplinary Research Fellow, MIT Media Lab
Multidisciplinary research fellow. Verifies domain-specific accuracy, terminology usage, and alignment with current knowledge in the field.
Dr. Priya Sharma
Impact Assessor
Former Nature Reviews Editor-in-Chief
Former Nature Reviews editor. Evaluates contribution significance, novelty of insights, practical implications, and publication readiness.
The Council
All 7 experts discuss, debate, and converge on a unified verdict for your document.
Three Phases. Complete Transparency.
Upload once. Seven experts take it from there.
Phase 1: Expert Review
Each of 7 agents independently scans your document from their specialty, producing individual scores and detailed findings.
Phase 2: Council Debate
Agents challenge, question, and build on each other's findings. Disagreements are resolved through evidence across 3 discussion rounds.
Phase 3: Final Report
Executive summary with weighted scores, verified fact-checks, identified gaps, and prioritized recommendations.
Why Multi-Agent Review?
Single-AI analysis sees one perspective. The Council sees seven.
7x the Coverage
Seven specialized perspectives catch issues that a single AI consistently misses. Each expert covers different blind spots.
Real-Time Debate
Agents challenge each other's findings in real-time discussion rounds, eliminating false positives and strengthening real findings with evidence.
Evidence-Based Verdict
The final report reflects where experts agreed (strong signals) and disagreed (nuanced issues) — backed by evidence, not averages.
Why Council vs. Standard AI Detection?
| Capability | Standard AI | Agentic Council |
|---|---|---|
| AI Agents | Single AI, one pass | 7 specialized agents |
| Analysis Method | One-shot analysis | Multi-pass investigation + debate |
| Fact-Checking | Surface-level | Dedicated expert with source verification |
| Citation Review | Format check only | Full source quality + completeness audit |
| Cross-Validation | None | 3 rounds of expert cross-examination |
| Report Output | Overall score only | Detailed report with evidence + recommendations |
Start Your First Council Review
See what 7 expert AI agents find in your document that single-pass detection misses.
Start Council Review