ThinkTank: A Framework for Generalizing Domain-Specific AI Agent Systems into Universal Collaborative Intelligence Platforms

2025-06-03

AI Summary

Vertical-domain AI agents struggle to collaboratively solve complex, cross-domain problems. Method: This paper proposes ThinkTank—a general collaborative intelligence platform enabling secure knowledge co-creation and sharing. It introduces a novel scientific collaboration paradigm for agent generalization: (1) role abstraction to decouple cross-domain capabilities; (2) an iterative, unified meeting protocol to model collaborative structures; and (3) integration of RAG with localized Ollama inference (Llama3.1) to ensure data privacy and sovereignty. Contribution/Results: First, it formalizes AI agents as reusable, composable collaborative units. Second, it significantly improves efficiency on knowledge-intensive tasks while reducing cloud dependency and deployment costs. Third, the framework is open-sourced and validated across multiple industry scenarios, demonstrating robust cross-domain collaboration and practical deployability.

Technology Category

• Humans and AI: Human-AI Collaboration / Human-AI Teaming
• Intelligent Robots: Embodied AI
• Cognitive Modeling & Cognitive Systems: Agent Architectures

Application Category

• Search and Retrieval-Augmented AI: Agentic search
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI

Abstract

This paper presents ThinkTank, a comprehensive and scalable framework designed to transform specialized AI agent systems into versatile collaborative intelligence platforms capable of supporting complex problem-solving across diverse domains. ThinkTank systematically generalizes agent roles, meeting structures, and knowledge integration mechanisms by adapting proven scientific collaboration methodologies. Through role abstraction, generalization of meeting types for iterative collaboration, and the integration of Retrieval-Augmented Generation with advanced knowledge storage, the framework facilitates expertise creation and robust knowledge sharing. ThinkTank enables organizations to leverage collaborative AI for knowledge-intensive tasks while ensuring data privacy and security through local deployment, utilizing frameworks like Ollama with models such as Llama3.1. The ThinkTank framework is designed to deliver significant advantages in cost-effectiveness, data security, scalability, and competitive positioning compared to cloud-based alternatives, establishing it as a universal platform for AI-driven collaborative problem-solving. The ThinkTank code is available at https://github.com/taugroup/ThinkTank

Problem

• Transforming specialized AI agents into universal collaborative platforms
• Generalizing agent roles and knowledge integration for diverse domains
• Enabling secure, scalable AI collaboration with local deployment

Innovation

• Generalizes agent roles and meeting structures
• Integrates Retrieval-Augmented Generation with knowledge storage
• Ensures data privacy via local deployment frameworks