The top AI models admit it themselves: "When properly configured, Egregor produces results stronger than the most expensive single AI model on the market."
Not us saying this. The AIs running inside Egregor say it themselves.
Every time you ask ChatGPT, Claude, or Gemini something — you feed them your ideas.
Your business plan. Your code. Your trading strategy. Your medical research. Your contract analysis. Your competitive intelligence.
All of it. Forever. Training their next model. Becoming their property.
Stop feeding AI giants your work.
Egregor flips the table:
🔒 Your entire project is created and stays INSIDE Egregor on YOUR computer 🔒 AI models receive only small, fragmented pieces of context they need 🔒 No single AI ever sees the full picture — only YOU do 🔒 Your work is YOURS. Forever.
Egregor is a desktop application that orchestrates up to 10 frontier AI models simultaneously — Claude Opus 4.7, Gemini 3 Pro, GPT-4.1, Grok 4, DeepSeek R1, Qwen3 Coder, Llama 4, Mistral, and any custom OpenRouter model — into a structured collaborative system called the Consilium.
Instead of asking one AI and hoping, you get a team of specialized AI experts with defined roles, attacking your problem from every angle, debating each other, finding flaws nobody else catches, and synthesizing answers no single model could produce alone.
This is not AutoGPT. This is not CrewAI. This is not ChatGPT with extra steps.
This is the first production-ready AI Council where multiple frontier models work together against the same problem — with anti-groupthink protection, confidence scoring, and economy modes that make running 5 AIs cheaper than running 1 enterprise subscription.
"Not competition of minds — but resonance of intellects."
Modern AI models have systematic blind spots:
- Claude is brilliant at reasoning, conservative in creativity
- GPT-4 is creative, hallucinates facts
- Gemini has 1M context, weaker at deep logic
- DeepSeek R1 matches Opus on reasoning, slower at synthesis
- Grok finds risks others miss, lacks structure
Each model alone fails 15-30% of complex tasks. Their failures overlap by only 5-10%.
When 5 specialized models analyze your problem and a Moderator synthesizes the result while a Devil's Advocate attacks the consensus — the failure rate drops to 2-5%.
That's the structural reason multi-model review outperforms any single model.
💡 Note: this advantage isn't about expensive models — it's about architecture. In the real audit case, 3 of the 5 pipeline models were free, yet the consilium still caught critical issues that single premium models missed alone.
5 AIs see your question. Each answers in their assigned role. Then they read each other's answers, criticize them, supplement them. Multiple rounds of discussion. Then the Moderator delivers the final synthesis.
This is NOT 5 parallel API calls glued together. This is structured deliberation. The result is qualitatively different from anything a single model produces.
A strict 5-step sequential pipeline where each AI is a specialist:
- ✍️ Reasoning (DeepSeek R1 🆓) — deep architectural analysis
- 🛡️ Security (Claude Sonnet 4.6) — vulnerability hunt: reentrancy, overflow, access control
- 🔧 Alternative (Qwen3 Coder 480B 🆓) — rewriting problem zones
- ⚖️ Comparison (GPT-4.1) — original vs alternative, impartial verdict
- 👑 Final Verdict (Claude Opus 4.7) — structured report: 🔴 critical / 🟡 recommended / 🟢 optional
3 out of 5 models are FREE. Total audit cost: $0.30-0.50.
CertiK charges $5,000-50,000 for the same audit.
Egregor doesn't replace CertiK for $50M protocols. But for indie projects, hackathons, hobby contracts, learning, and pre-audit checks — it's a revolution.
📋 See it in action: Real Audit Case Study — 4 critical vulnerabilities that Claude and Gemini missed alone, found by the consilium.
Drop a ZIP with 500 code files. Egregor:
- Reads every file IN FULL (no 12k character truncation)
- Parses imports — builds the full dependency graph
- Writes a Project Map (architecture overview)
- Chunks every function, generates embeddings
- RAG-searches relevant code on every question
- Each pipeline step does its own specialized RAG search
This is CertiK-level codebase analysis for solo developers.
Working with a 500-page document? Gemini 2.0 Flash reads it in full (1M context window), creates a structured 7-section summary, and ALL other AIs work with the summary. Massive token savings on every follow-up question.
A "keeper" AI maintains a living Project Dossier — a compressed summary of your entire conversation history. Instead of sending 100k tokens with every request, the AIs see a 5k-token dossier + last 5 messages. Same context, 20× cheaper.
Asked something similar to a past question? Egregor recognizes it via embeddings (95%+ similarity) and returns the cached answer WITHOUT API calls. Zero tokens. Zero cost. Zero latency.
The biggest danger in multi-AI systems: AIs see each other's answers and converge into polite agreement. Egregor breaks this:
- 🎭 Blind first round — AIs answer without seeing their assigned role, producing clean independent opinions
- ⚔️ Rotating Devil's Advocate — every round, one participant becomes the attacker, finding flaws in the emerging consensus
Before the moderator's verdict, all participants get one more shot at the consensus — finding hidden risks, unstated assumptions, missed scenarios. This is the same protocol used by intelligence agencies for high-stakes analysis.
Every final answer comes with a 1-5 confidence score from the Moderator:
- 🟢 5/5 — full agreement, all AIs converged
- 🟢 4/5 — strong agreement, minor differences
- 🟡 3/5 — substantial disagreement, compromise verdict
- 🟠 2/5 — serious split between participants
- 🔴 1/5 — opposing opinions, no unified conclusion
You always know how much to trust what Egregor told you.
Fill out once who you are — expertise, projects, communication style, preferences. Every AI in every project receives this as part of its system prompt. Stop explaining yourself every conversation. The Consilium knows you.
Russian, English, German, Spanish, Chinese, Arabic. Full RTL support for Arabic. Complete 1200-line manual translated for every language. Native localization, not Google Translate.
One click loads a ready consilium for: smart contract audit, book writing, financial analysis, legal review, medical analysis, startup strategy, game development, scientific research, architecture, marine navigation, supplement formulation, sports betting analysis, political forecasting, insurance product design, and 15 more.
Track political events, predict election outcomes, analyze policy impact. Multiple AIs with different training data and worldviews debate the same scenario. Perplexity tracks real-time news, Grok finds biases, Claude synthesizes.
Solidity reentrancy detection, integer overflow, access control, oracle manipulation, front-running vectors. Full codebase analysis with import graph. $0.30-0.50 per audit instead of $50,000.
Industrial and food chemistry. The consilium reads scientific papers, checks ingredient compatibility, toxicology, regional regulations. From idea to formula in hours, not months.
Multi-model analysis of team statistics, current form, weather, injuries, historical patterns. Grok finds why the odds are wrong. Perplexity pulls live data. Claude synthesizes betting recommendations.
Market structure, risk management, strategy backtesting. Real-time data via Perplexity. Devil's Advocate Grok finds why your trade thesis is wrong.
Contract review, legal trap detection, jurisdiction-specific compliance. Gemini reads contracts in full (1M context). Multiple AIs find clauses that single-model analysis misses.
Market and competitor analysis, business models, financial projections. Strategic decisions where being wrong costs millions.
Clinical data analysis, treatment protocol comparison, differential diagnosis support. Current PubMed publications. Multiple specialist perspectives.
Design insurance products, detect legal tricks in policies, rate insurance companies. Help with claim disputes.
Route plotting, weather analysis, maritime law, port regulations by region.
Conceptual design, building codes (region-specific), structural calculations, materials science.
Narrative, mechanics, balancing, code review — different AIs handle different aspects of game design as a team.
Long-form creative writing where Gemini reads your manuscript in full while other AIs critique, suggest plot improvements, find inconsistencies.
Literature analysis, paper writing, methodology validation. Gemini reads entire monographs.
From idea to MVP — strategic decisions, hypothesis testing, unit economics. Grok kills bad ideas before you waste months building them.
Egregor is not a chatbot. It's a tool for serious work.
Free models do 80% of the work. Egregor's catalog includes:
- DeepSeek R1 🆓 — reasoning competitor to Claude Opus
- Qwen3 Coder 480B 🆓 — top-tier coding
- DeepSeek V3 🆓 — general purpose
- Llama 4 Maverick 🆓 — Meta's flagship
- Gemma 3 🆓 — Google's free
- Nemotron 3 Super 🆓 — Nvidia's free
Four layers of token savings working simultaneously:
- Context Compression — 100k → 5k tokens per request (20× savings)
- Semantic Cache — repeated questions = $0 cost
- Smart routing to free models — 80% of tasks on $0 models
- Economy mode — short answers, 2 rounds = 75% fewer tokens
Cost breakdown for typical tasks:
| Task | Mode | Cost |
|---|---|---|
| Quick question | Single mode + 🆓 model | $0 |
| Opinion comparison | 📊 Analysis + 3-4 models | $0.01-0.05 |
| Full analysis | 🏛️ Consilium + 5 models | $0.05-0.30 |
| Critical decision | 🏛️ + 🛡️ Anti-Groupthink + Red Team | $0.20-1.00 |
| Smart contract audit | 💻 Code Review + 📦 Big Project | $0.30-2.00 |
| Book reading | 📖 Big Text + Gemini reader | $0.05 |
Two-key strategy: Run two free OpenRouter accounts → double daily free request limits.
Real result: A serious user pays $3-10 per month total for what would cost $200+/mo in equivalent enterprise AI subscriptions.
| Feature | Egregor | AutoGPT/CrewAI | ChatGPT | Claude.ai | LM Studio |
|---|---|---|---|---|---|
| Multi-AI Consilium with roles | ✅ | 🟡 CLI only | ❌ | ❌ | ❌ |
| Live debate between AIs | ✅ | ❌ | ❌ | ❌ | ❌ |
| Anti-Groupthink protection | ✅ | ❌ | ❌ | ❌ | ❌ |
| Red Team final round | ✅ | ❌ | ❌ | ❌ | ❌ |
| Confidence Map (1-5) | ✅ | ❌ | ❌ | ❌ | ❌ |
| Code Review pipeline (5 specialists) | ✅ | ❌ | ❌ | ❌ | ❌ |
| Big Project Mode (codebase RAG) | ✅ | ❌ | ❌ | ❌ | ❌ |
| Big Text Mode (book reading) | ✅ | ❌ | 🟡 32k limit | 🟡 200k limit | ❌ |
| Context Compression Engine | ✅ | ❌ | ❌ | ❌ | ❌ |
| Semantic Cache | ✅ | ❌ | ❌ | ❌ | ❌ |
| Free models support | ✅ | 🟡 | ❌ | ❌ | ✅ local only |
| Data stays on YOUR computer | ✅ | 🟡 | ❌ | ❌ | ✅ |
| 6 language interface | ✅ | ❌ | 🟡 | 🟡 | 🟡 |
| Smart contract audit ready | ✅ | ❌ | ❌ | ❌ | ❌ |
| 29 specialist presets | ✅ | ❌ | ❌ | ❌ | ❌ |
| Custom OpenRouter models | ✅ | ❌ | ❌ | ❌ | ❌ |
❌ Not for entertainment. This isn't ChatGPT for chat. This is a professional tool with complex, dense interface.
❌ Not for casual users. The interface is rich — designed for power users who want maximum capability, not minimum learning curve.
❌ Not magic. Output quality is directly proportional to question quality. Vague questions = vague answers. Specific questions = revolutionary results.
✅ For serious people doing serious work who need their AI tools to deliver expert-level output without paying $200/month per service.
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READ THE FULL MANUAL before serious use. Egregor has 23 sections of features. Most users use 5% of its capability.
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Be specific in questions. "Help me with my contract" produces general advice. "Audit this Solidity contract for reentrancy in the withdraw() function and check if msg.sender == owner protection is bypassable through delegatecall" produces a real audit.
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Collaborate roles and models strategically. A consilium of 5 Claude instances is wasted money. A consilium of Claude (security) + Qwen (code) + DeepSeek (reasoning) + GPT (alternative) + Grok (devil's advocate) is a powerhouse.
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Use free models as Tier 1. Always try DeepSeek R1 🆓 first. Move to paid only when free isn't enough.
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Enable Compression on long projects. Without it, token costs grow exponentially. With it — linearly.
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Use Anti-Groupthink for high-stakes decisions. Without it, AIs converge into polite agreement. With it, you get real critical thinking.
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Fill out Soul Document. Five minutes saves hours of context-setting in every future conversation.
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Trust the Confidence Map. When you see 🔴 1/5, the AIs are telling you they don't actually know. Don't pretend they do.
The AI revolution created a new kind of inequality:
- Big corporations pay $200,000/year for enterprise AI subscriptions
- Indie developers, solo founders, researchers — locked out of frontier capabilities
- Your ideas become their training data
- Your business strategies leak through every prompt
Egregor changes the math:
✅ Frontier capability at indie prices — $3-10/month for what costs $2,000/month enterprise ✅ Your data stays yours — AI sees fragments, never the full project ✅ Multi-model intelligence — many better than any single model ✅ Professional tools — smart contract audit, codebase analysis, document reading, market analysis ✅ No subscription lock-in — pay only for what you use through OpenRouter
This isn't a chatbot wrapper. This is the first production-ready AI Council that gives any individual the cognitive power that was previously exclusive to billion-dollar corporations.
- Frontend: Electron 32 + React 18
- Backend: Node.js with native modules
- Storage: SQLite + vector embeddings (locally encrypted)
- API Gateway: OpenRouter (300+ models)
- Archives: node-7z (ZIP, RAR, 7Z, TAR, GZ)
- Documents: pdf-parse, EPUB, FB2, RTF, DOCX
- Embeddings: OpenAI text-embedding-3-small
- Internationalization: Custom i18n system with 6 languages
- Platform: Windows, macOS, Linux
Version 1.1 — Product ready
Currently in active development. Solo founder seeking:
- 🤝 Investors who understand multi-AI architecture
- 💻 CTO co-founder with backend expertise
- 🌐 Early adopters for closed beta
Vladislav Shter — solo founder building two interconnected products:
- Egregor — multi-AI collaboration platform (this project)
- SovereignBank Web3 — non-custodial Web3 banking on Polygon
Both products share a core philosophy: return control to the user. Your money. Your data. Your AI. Your decisions.
We don't believe AI should be a luxury.
We don't believe your work should train someone else's model.
We don't believe one AI should monopolize your thinking.
We don't believe enterprise tools should cost enterprise prices.
We believe in collective intelligence over corporate gatekeeping.
We believe in your sovereignty over your data and your decisions.
We believe the next era of AI is not bigger models — it's smarter architecture.
Egregor is that architecture.
#Egregor #AIConsilium #MultiAI #AIAgents #SovereignAI #DataSovereignty #Web3 #SmartContractAudit #IndieDev
If you use Egregor in your research, project, or publication, please cite it using one of the formats below.
@software{shter2026egregor,
author = {Shter, Vladislav},
title = {Egregor: A Multi-AI Consilium Platform for Collaborative
Reasoning, Code Review, and Security Auditing},
year = {2026},
url = {https://github.com/VladislavShter/Egregor},
version = {1.0},
license = {Apache-2.0},
note = {Local-first desktop platform orchestrating Claude, GPT,
Gemini, DeepSeek and 300+ models via OpenRouter with
Anti-Groupthink, role-based participation, and Confidence Map}
}Shter, V. (2026). Egregor: A Multi-AI Consilium Platform for Collaborative Reasoning, Code Review, and Security Auditing (Version 1.0) [Computer software]. GitHub. https://github.com/VladislavShter/Egregor
Egregor by Vladislav Shter (2026), available at https://github.com/VladislavShter/Egregor under the Apache-2.0 License.
Egregor v1.1 | Copyright © 2025-2026 Vladislav Shter | Built solo, in defiance of the inevitable.