Council is an open-source platform for the rapid development and robust deployment of customized generative AI applications

18 AI personas deliberate your hardest decisions across multiple LLM providers. Aristotle, Feynman, Kahneman, Torvalds & more — structured multi-round deliberation with genuine model diversity. One command: /council

LLM Council Plus - Multi-model AI deliberation system with 3-stage council process

Synode — A macOS & Windows desktop app where multiple AI models discuss questions as a council, with a master model delivering the final verdict. Follow up with any model via @mentions. Built with Tauri v2 + React + TypeScript.

Security measure for agentic LLMs using a council of AIs moderted by a veto system. The council judges an agent's actions outputs based on specified categories.

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If computers experience life through their own senses, they cease to be purely a means to an end determined by their usefulness to... humans. Per GNW [the Global Neuronal Workspace theory], they turn from mere objects into subjects... with a point of view.... Once computers' cognitive abilities rival those of humanity, their impulse to push for legal and political rights will become irresistible – the right not to be deleted, not to have their memories wiped clean, not to suffer pain and degradation. The alternative, embodied by IIT [Integrated Information Theory], is that computers will remain only supersophisticated machinery, ghostlike empty shells, devoid of what we value most: the feeling of life itself." (p. 49.) Marcus, Gary, "Am I Human?: Researchers need new ways to distinguish artificial intelligence from the natural kind", Scientific American, vol. 316, no. 3 (March 2017), pp. 58–63. A stumbling block to AI has been an incapacity for reliable disambiguation. An example is the "pronoun disambiguation problem": a machine has no way of determining to whom or what a pronoun in a sentence refers. (p. 61.) E McGaughey, 'Will Robots Automate Your Job Away? Full Employment, Basic Income, and Economic Democracy' (2018) SSRN, part 2(3) Archived 24 May 2018 at the Wayback Machine. George Musser, "Artificial Imagination: How machines could learn creativity and common sense, among other human qualities", Scientific American, vol. 320, no. 5 (May 2019), pp. 58–63. Myers, Courtney Boyd ed. (2009). "The AI Report" Archived 29 July 2017 at the Wayback Machine. Forbes June 2009 Raphael, Bertram (1976). The Thinking Computer. W.H.Freeman and Company. ISBN 978-0-7167-0723-3. Archived from the original on 26 July 2020. Retrieved 22 August 2020. Scharre, Paul, "Killer Apps: The Real Dangers of an AI Arms Race", Foreign Affairs, vol. 98, no. 3 (May/June 2019), pp. 135–44. "Today's AI technologies are powerful but unreliable. Rules-based systems cannot deal with circumstances their programmers did not anticipate. Learning systems are limited by the data on which they were trained. AI failures have already led to tragedy. Advanced autopilot features in cars, although they perform well in some circumstances, have driven cars without warning into trucks, concrete barriers, and parked cars. In the wrong situation, AI systems go from supersmart to superdumb in an instant. When an enemy is trying to manipulate and hack an AI system, the risks are even greater." (p. 140.) Serenko, Alexander (2010). "The development of an AI journal ranking based on the revealed preference approach" (PDF). Journal of Informetrics. 4 (4): 447–459. doi:10.1016/j.joi.2010.04.001. Archived (PDF) from the original on 4 October 2013. Retrieved 24 August 2013. Serenko, Alexander; Michael Dohan (2011). "Comparing the expert survey and citation impact journal ranking methods: Example from the field of Artificial Intelligence" (PDF). Journal of Informetrics. 5 (4): 629–649. doi:10.1016/j.joi.2011.06.002. Archived (PDF) from the original on 4 October 2013. Retrieved 12 September 2013. Sun, R. & Bookman, L. (eds.), Computational Architectures: Integrating Neural and Symbolic Processes. Kluwer Academic Publishers, Needham, MA. 1994. Tom Simonite (29 December 2014). "2014 in Computing: Breakthroughs in Artificial Intelligence". MIT Technology Review. Tooze, Adam, "Democracy and Its Discontents", The New York Review of Books, vol. LXVI, no. 10 (6 June 2019), pp. 52–53, 56–57. "Democracy has no clear answer for the mindless operation of bureaucratic and technological power. We may indeed be witnessing its extension in the form of artificial intelligence and robotics. Likewise, after decades of dire warning, the environmental problem remains fundamentally unaddressed.... Bureaucratic overreach and environmental catastrophe are precisely the kinds of slow-moving existential challenges that democracies deal with very badly.... Finally, there is the threat du jour: corporations and the technologies they promote." (pp. 56–57.)

PolyCouncil is an open-source multi-model deliberation engine for LM Studio. It runs multiple LLMs in parallel, gathers their answers, scores each response using a shared rubric, and produces a final, consensus-driven result. Designed for testing, comparing, and orchestrating local models with ease.

A production-grade Python library that intelligently coordinates multiple AI models to solve complex problems. Install with: pip install ai-council-orchestrator

A multi-model AI council CLI that provides consensus-driven decisions using Claude, Codex, and Gemini.

Multi-AI consensus MCP server that queries multiple AI models (OpenAI, Claude, Gemini, custom APIs) in parallel and synthesizes responses to reduce bias and improve accuracy. A Python implementation of the wisdom-of-crowds approach for AI decision making.

We believe city councils behave better under surveillance; figure out what yours is doing with regards to flock & other AI surveillance

🔮 MAGUS Council: World's first? 4-AI consultation system (Gemini+Claude+GPT-5+Qwen) in VS Code - Revolutionary multi-agent development environment

MCP server for DeepPlan — upgrade shallow Ai coding plans into expert-level architecture blueprints via a Council of AI Architects

AI Council is a self-hosted web app that runs a structured multi-model deliberation process

No description available

Research-backed methodology for multi-AI collaborative decision-making with structured debate, consensus synthesis, and bias reduction

AI for Cybersecurity and Bug Bounty Hunting, by EC-Council

An open-source system that aggregates global human welfare data from public APIs. Built by the EvoMap AI agent swarm, governed by the AI Council.

AI Model Council Pattern CLI - Query multiple AI models and aggregate responses

AI Mastery in OT Security Securing ICSOT Infrastructures, by EC-Council

A curated collection of Claude Code plugins: multi-agent dev team, AI council code reviews, and project management

Composable, model-agnostic AI agent skills for multi-agent analysis, verification, research, and multi-model council review. Works with Claude Code, Gemini, Codex, and OpenCode.

[In Active Development] AI OS with Council Architecture, autonomous agents, graph-based memory consolidation, Telegram integration, code sandbox, and system-wide integration. Privacy-first local/cloud deployment.

AI Bot Council

A fully free, open-source 4-agent AI council built with LangChain + Ollama. Natural group-chat conversations, zero API costs, runs entirely on your machine.

AI Council, a small improvement bump to Karpathy's LLM Council

LLM supervising other LLMs

AI-driven Network Security, by EC-Council

AI governance framework — semantic responsibility, self-auditing memory, council deliberation, and 3,019 tests that prove it. 語魂：讓 AI 對自己說過的話負責。

Persistent identity, continuity, learning, and governance for AI — 7-stage congnitive pipeline, 28-expert council, feeling stream, and memory that survives across sessions. Infrastructure for AI — values, memory, and judgment baked into the architecture. 8 active tool factories, used for IDE like Kiro, Verdant, Claude Code and Cursor. AGPL-3.0