How to Build Custom AI Agents and Workflows Without Code Using Stack AI
Building a custom AI assistant or automation used to require deep engineering skills and months of work. Stack AI changes that with a visual, no-code platform where you connect your data and tools to large language models to create production-ready AI agents. This tutorial shows you how to build your first AI workflow with Stack AI.
Step 1: Define your use case
Start with a clear problem, such as answering customer questions from your help documents, automating research, or processing incoming documents. A well-defined use case tells you what data you need and what output you expect, which keeps your build focused.
Step 2: Create a project in Stack AI
Log in to Stack AI and create a new project. You will see a visual canvas where you can drag and drop components to build a pipeline. Familiarize yourself with the available nodes for inputs, LLMs, data retrieval, and outputs.
Step 3: Connect your data sources
Add connectors to the services holding your information, such as your knowledge base, a database, cloud storage, or a CRM. Stack AI lets you ingest documents and set up retrieval-augmented generation (RAG) so the AI can answer questions by pulling from your actual content, not just generic training data.
Step 4: Assemble your AI workflow
On the canvas, connect the nodes to build your flow: receive a user question, retrieve relevant context from your connected data, send it to an LLM with your instructions, and return a grounded answer. For more advanced agents, add steps for multiple tools, function calls, or human-in-the-loop approval before the workflow takes action.
Step 5: Test and refine
Run test queries to see how your agent responds. Refine your system prompts, adjust which data sources are queried, and improve the output formatting until the agent answers accurately and reliably. Test edge cases so production answers stay high quality.
Step 6: Deploy and monitor
When you are satisfied, deploy your agent as a chat widget, API, or integrated assistant. Use Stack AI’s analytics to see how it performs in the real world, and iterate on the flow based on user questions and feedback. Because it is no-code, you can continually improve the agent without a development cycle.
With Stack AI, non-engineers can ship enterprise-grade AI agents in days, turning internal knowledge and workflows into automated, always-available assistance.
