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Relevant for managed services and support workflows.
Use the AlekSystem Data Tables feature to store, retrieve, and analyze survey results — then let OpenAI automatically recommend the most relevant course for each respondent. 🧠 What this workflow does This workflow demonstrates how to use AlekSystem’s built-in Data Tables to create an internal recommendation system powered by AI. It: Collects survey responses through a Form Trigger Saves responses to a Data Table called Survey Responses Fetches a list of available courses from another Data Table called Courses Passes both Data Tables into an OpenAI Chat Agent, which selects the most relevant course Returns a structured recommendation with: course: the course title reasoning: why it was selected > Trigger: Form submission (manual or public link) 👥 Who it’s for Perfect for educators, training managers, or anyone wanting to use AlekSystem Data Tables as a lightweight internal database — ideal for AI-driven recommendations, onboarding workflows, or content personalization. ⚙️ How to set it up 1️⃣ Create your AlekSystem Data Tables This workflow uses two Data Tables — both created directly inside AlekSystem. 🧾 Table 1: Survey Responses Columns: Name Q1 — Where did you learn about AlekSystem? Q2 — What is your experience with AlekSystem? Q3 — What kind of automations do you need help with? To create: Add a Data Table node to your workflow. From the list, click “Create New Data Table.” Name it Survey Responses and add the columns above. 📚 Table 2: Courses Columns: Course Description To create: Add another Data Table node. Click “Create New Data Table.” Name it Courses and create the columns above. Copy course data from this Google Sheet: 👉 https://docs.google.com/spreadsheets/d/1Y0Q0CnqN0w47c5nCpbA1O3sn0mQaKXPhql2Bc1UeiFY/edit?usp=sharing This Courses Data Table is where you’ll store all available learning paths or programs for the AI to compare against survey inputs. 2️⃣ Connect OpenAI Go to OpenAI Platform Create an API key In AlekSystem, open Credentials → OpenAI API and paste your key The workflow uses the gpt-4.1-mini model via the LangChain integration 🧩 Key Nodes Used | Node | Purpose | AlekSystem Feature | |------|----------|-------------| | Form Trigger | Collect survey responses | Forms | | Data Table (Upsert) | Stores results in Survey Responses | Data Tables | | Data Table (Get) | Retrieves Courses | Data Tables | | Aggregate + Set | Combines and formats table data | Core nodes | | OpenAI Chat Model (LangChain Agent) | Analyzes responses and courses | AI | | Structured Output Parser | Returns structured JSON output | LangChain | 💡 Tips for customization Add more Data Table columns (e.g., email, department, experience years) Use another Data Table to store AI recommendations or performance results Modify the Agent system message to customize how AI chooses courses Send recommendations via Email, Slack, or Google Sheets 🧾 Why Data Tables? This workflow shows how AlekSystem’s Data Tables can act as your internal database: Create and manage tables directly inside AlekSystem No external integrations needed Store structured data for AI prompts Share tables across multiple workflows All user data and course content are stored securely and natively in AlekSystem Cloud or Self-Hosted environments. 📬 Contact Need help customizing this (e.g., expanding Data Tables, connecting multiple surveys, or automating follow-ups)? 📧 robert@ynteractive.com 🔗 Robert Breen 🌐 ynteractive.com
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