💰 Cash Prizes: $1k for 1st, $500 for 2nd, and $250 for 3rd place.

🌐 Engage with a vibrant community: Collaborate, discuss, and share your workflows.

✅ Use provided datasets to address challenges in entrepreneurship, small businesses, big industries, and SecOps.

🎖 Judged on impact, efficacy, and complexity of solutions.

Looking to collaborate? Join our Discord & Community Forums

Creating LLM apps with n8n and LangChain

Learn more about n8n’s LangChain integration

LangChain Docs

Rules

• We provide participants with 4 real-world problems and challenge them to solve them using the AI Langchain feature in their workflow.
• They must use the AI LangChain nodes and the provided resources to resolve 1 of the 3 problems
• Multiple submissions are allowed
• Collaboration and sharing of workflows for feedback (before final submission) within the community are encouraged.
• Bonus points for creative thinking

Criteria for Judging:

• Impact and relevance of the problem addressed
• Efficacy of the proposed solution
• Complexity and adept use of the AI LangChain feature

Resources Provided:

• A dataset containing common business problems (like inventory data, customer service queries, etc.).
• Community channel on forum and Discord for participants to discuss ideas and share feedback.
• Typeform for submission of template

CHOOSE FROM ONE OF THE BELOW DATASETS

Entrepreneur Business Problems

Problem: Predicting the success of online campaigns based on historical data and AI analysis.

Download the below file to tackle this challenge

Digital Marketing Analytics (SuperCheeky.inc).xlsx

Small Business Problems

Problem: Personalizing marketing emails based on customer purchase history.

Download the below file to tackle this challenge

Online Merch Store (n8n FanClub Merch.io).xlsx

Big Industry Business Problems:

Problem: Optimizing warehouse logistics using predictive analysis based on purchase and return data.

Download the below file to tackle this challenge

E-Commerce Returns _ Inventory (Auto-Matey.io).xlsx

SecOps Business Problem:

Automated Threat Intelligence Correlation & Response

Problem: With the volume of security alerts that modern Security Information and Event Management (SIEM) tools generate, it becomes challenging for SecOps teams to efficiently correlate these alerts, prioritize them, and formulate a rapid response. The challenge is to use LLM's and Langchain to automatically correlate threat intelligence from multiple sources, prioritize alerts based on threat severity, and suggest or initiate automated responses.

Download the below file to tackle this challenge

SecOps Secuirty Alerts.xlsx

Submit your workflow templates for the contest below or via this link: https://n8n-community.typeform.com/to/I3LvKzaa

https://n8n-community.typeform.com/to/I3LvKzaa

Conditions of participation

Index

• Conditions of participation
• Scope/content of the competition