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AI n8n Automation Collective is a beginner-friendly community to learn how to use AI, n8n, and other automation tools to eliminate repetitive work.
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47 contributions to AI n8n Automation Collective
6d •
Hedge Fund in-a-box!
Someone just created a hedge fund model using AI agents. A rapidly trending open-source Python project called “Trading Agents” simulates an entire hedge fund using multiple LLM-powered agents. Instead of a single model making decisions, it mirrors how real trading firms operate—with specialized roles that analyze, debate, and approve trades collaboratively. The framework breaks down a trading firm into distinct AI agents: 1. Analyst Layer (parallel execution) - Fundamentals analyst → financials & valuation - Sentiment analyst → social/media mood - News analyst → macro + breaking events - Technical analyst → indicators (MACD, RSI, etc.) Each produces independent reports—disagreement is intentional and valuable. 2. Research Layer (debate engine) - Bull agent vs. Bear agent - They argue over multiple rounds using analyst data - Designed to surface stronger, more defensible conclusions 3. Decision Layer - Trader agent → decides timing & position size - Risk management → evaluates volatility/liquidity - Portfolio manager → final approval/rejection If approved → simulated trade executesIf rejected → system logs reasoning Unlike traditional trading systems: - Not purely rule-based - Not a black-box ML model Instead, it’s: - Transparent & auditable - Every decision is traceable: Analyst reports Debate transcripts Trade rationale Approval/rejection logic Technical Backbone - Built in Python using LangGraph (agent orchestration) - Each agent = node in a decision graph - Features: Checkpointing (resume runs) Persistent decision logs Self-reflection loop: Tracks past trades Compares performance vs. benchmarks Feeds insights back into future decisions Recent Updates (v0.2.4) - Structured outputs using schemas (more reliable decisions) - Expanded model support (OpenAI, Gemini, Claude, DeepSeek, etc.) - Docker support - Standardized rating system: Buy / Overweight / Hold / Underweight / Sell
2 likes • 5d
@Michele McDermott working on it!
0 likes • 8h
I put it online so anybody can try it out: https://dev.signaldesk.technology/
8d •
Retell AI - Automated call agents
I've been playing with Retell AI (retellai.com) lately and am quite impressed. The agents sound and act more or less human (a little scary actually) and the workflow building right inside Retell is impressive! If you're a strong prompt engineer and workflow builder, this system could replace a whole call center within a week.
0 likes • 6d
For anyone interested in seeing how Fortune 500 companies use Retell (I'm not affiliated with them in any way): https://us06web.zoom.us/webinar/register/WN__7Ns1Dw7RUyAZeGFfoJtzQ?u#/registration
8d •
START HERE! Activity Tracker
You can't start automating if you don't know what to automate. 1. Use the below template to track what you do each day: https://docs.google.com/spreadsheets/d/1j4O_4UGqPvrGPRTygecagRxosbvjxpsQE8ivwCZdwn0/copy 2. Once finished, throw it into the LLM with the following prompt: "As an AI expert, help me find ways to leverage AI and automation to make my operations more efficient and free up my time. For the initial delivery, review the attached activity tracker of what I do during the day. Based on this, come up with the following: 1. Pain summary - One or two sentences summarizing my pain points and bottlenecks 2. Outcome - Two or three sentences summarizing areas for improvement and estimated time (hours a week) that I can reclaim and estimated financial impact. 3. List of recommended solutions to achieve the outcomes mentioned in 2, including estimated costs for each. 4. A 4-day quick win plan on how the venue and its personnel can implement some (or all) of the recommended solutions" 3. Start automating! Bonus Tip: If the activity tracker is going to be too much work, have a voice chat with your favorite LLM instead and have it ask you what you do on a daily basis. Sample prompt: "As an AI expert, you are to help me find ways to leverage AI and automation to make my operations more efficient and free up my time. For the initial delivery, have a 10 minute voice chat with me asking me various questions about what I do each day based on achieving the below outputs. Based on chat, come up with the following: 1. Pain summary - One or two sentences summarizing my pain points and bottlenecks 2. Outcome - Two or three sentences summarizing areas for improvement and estimated time (hours a week) that I can reclaim and estimated financial impact. 3. List of recommended solutions to achieve the outcomes mentioned in 2, including estimated costs for each. 4. A 4-day quick win plan on how the venue and its personnel can implement some (or all) of the recommended solutions
0 likes • 8d
Sample Output: 1. Pain Summary XXXX is spending significant time manually responding to repetitive inquiries and managing post-booking follow-ups using fragmented, mostly manual processes. The lack of automation across intake, communication, and project tracking is creating unnecessary administrative overhead. 2. Outcome (Efficiency + Impact) By automating inquiry responses, standardizing workflows, and introducing lightweight project automation, the venue can eliminate most repetitive communication and follow-up tasks. - Estimated time savings: 10–18 hours/week (primarily admin + communication time) - Financial impact: ~$8,000–$20,000/year in labor cost savings (assuming $20–$30/hr blended admin rate) Additional upside: faster response times → higher conversion rates (typically +10–25% for venues) Operationally, this shifts staff from reactive admin work → higher-value activities (sales, upselling, client experience). 3. Recommended Solutions (Practical Stack + Cost) A. AI Inquiry Response Automation (Highest ROI) What it does: - Auto-reads inbound inquiries (email/form) - Classifies intent (pricing, availability, brochure, custom) - Sends tailored responses instantly using templates + variables Tools: - Zapier or Make (Integromat) - OpenAI API - Gmail / Outlook integration Cost: - $30–$150/month (depending on volume) Impact: - Eliminates ~70–80% of inquiry response time - Reduces response time from hours → seconds B. Smart Email Templates + CRM Light Layer What it does: - Centralizes templates (no more copy/paste from files) - Auto-fills client name, event type, date, etc. - Tracks conversations Tools: - HubSpot CRM (free tier works) - Or Streak CRM (simpler) Cost: - Free → $50/month Impact: - Removes manual searching/copying of templates - Adds visibility into pipeline (often missing in venues) C. Automated Contract + Booking Workflow What it does: - Sends contract automatically after qualification - Tracks signing status - Triggers next steps automatically once signed
10d •
GPT 5.5. Thoughts?
Has anybody had the chance to play with GPT 5.5 yet? Initial thoughts?https://openai.com/index/introducing-gpt-5-5/
27d •
Who here is using Claude + n8n together in their stack?
Show of hands — who's actually using Claude daily alongside n8n? And if so, what's your #1 use case? I've been building some crazy multi-agent workflows where Claude handles reasoning and n8n handles orchestration. The combo is insane. Curious what setups others in here are running.
0 likes • 10d
I'm a big fan of Claude myself, but I can't ignore the latest GPT 5.5 benchmark results.
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Joined Aug 20, 2025