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Ace Intelligence Systems
Preparing a calmer, clearer view of your automation workspace.
Aligning workflows
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Preparing a calmer, clearer view of your automation workspace.
Ace Intelligence
An advanced autonomous multi agent research platform powered by n8n orchestration. 8 specialized AI agents collaborate to transform a research topic into a comprehensive academic paper.
Version 8.0, Production Ready, Single Unified Workflow. This system represents a sophisticated deep engineering build that automates the lifecycle of complex research. It relies on LangGraph principles to orchestrate multi agent workflows, featuring specialized discovery agents, systematic literature review capabilities, and strict hallucination reducing verification layers. The modular pipeline integrates external APIs like arXiv and Semantic Scholar alongside ChromaDB for robust vector memory and RAG.
The system runs as a unified n8n workflow. Submit a research topic via the frontend, and 8 agents autonomously execute the full research lifecycle.
Orchestrator: State initialization and management via Code Node. Keyword Generator: Academic search keyword generation using LLaMA 3.3 70B. Researcher: Literature search and discovery via HTTP/API. Strategist: Gap identification and research strategy using LLaMA 3.3 70B. Architect: Methodology design using LLaMA 3.3 70B. Implementer: Data and implementation planning using LLaMA 3.3 70B. Analyst: Experiment design using LLaMA 3.3 70B. Editor: Final paper compilation using LLaMA 3.3 70B.
Phase 1, Initialization: Webhook trigger receives topic from frontend, initializes research state. Phase 2, Research Intelligence (Agents 1 to 3): Keyword generation, web search via DuckDuckGo, literature review with theme identification. Phase 3, Strategy and Methodology (Agents 4 to 5): Gap statement formulation, research questions, methodology design. Phase 4, Implementation and Experiments (Agents 6 to 7): Data requirements planning, experimental framework design. Phase 5, Quality and Compilation (Agents 7 to 8): Novelty and ethics validation, IEEE format paper generation. Phase 6, Response: JSON formatted output with complete paper and execution metadata.
Endpoint: POST http://localhost:5678/webhook/start-research. Request body: { 'topic': 'Your Research Topic' }. Response includes the full generated paper content, execution time, agents executed, and phase completion status.
POST /webhook/start-research
Request: { "topic": "Your Topic" }
Response: { "success": true, "content": "# Paper...", "metadata": { "executionTimeSeconds": 90, "agentsExecuted": 8 } }This project serves as our ultimate proof of technical capability. While rapid deployment automations act as the 'Trojan Horse' for initial trust, this system is the high ticket upsell. It proves to enterprise organizations that we can move beyond simple chatbots to deploy autonomous agents that research, reason, verify facts, and execute multi step tasks securely at scale. Falls under our Custom Generative AI & Conversational Agents category, a flagship example for Multi Agent Workflows and Enterprise RAG Architectures.
Explore the full n8n workflow JSON, frontend code, and deployment configuration.
https://github.com/OMCHOKSI108/AI-AUTOMATION-WORKFLOWSBuilt by the Ace Intelligence founding team.
Om Choksi (CTO) — https://github.com/OMCHOKSI108
Yash Khare (Founder) — https://github.com/firefistisdead
Ansh Gajera (CEO) — https://github.com/anshgajera