Stack AI
Workflow platform
Stack AI lets me design, test, and deploy AI automations without reinventing glue code. Think of it as a node-based builder where you wire models, data sources, tools, and actions into repeatable flows, then run them on managed infrastructure or trigger them via API/webhooks. (stack-ai.com)
Why I use it
- Rapid prototyping. Chain together prompts, retrieval, and actions visually, then flip to code view when you need custom logic.
- Production-ready. Built-in hosting, scheduling, API endpoints, and logs mean you can ship internal tooling or lightweight products fast.
- Integrations + tools. Connect to data sources, CRMs, Slack, Notion, email, or your own APIs so the agent can actually do work.
- Collaboration. Share projects with teammates, reuse components, and maintain versions without patching YAML everywhere.
Typical plays
- Agent automations. Spin up onboarding agents, lead qualifiers, or research assistants that combine LLM reasoning with your internal knowledge bases.
- Workflow APIs. Expose a Stack AI flow as an API endpoint and call it from your product or Zapier.
- Internal ops. Automate reporting, ticket triage, or update cycles without building a full backend.
Getting started
- Sign up at stack-ai.com and create a workspace.
- Use the canvas to add nodes (LLMs, tools, data sources) and connect them with branches/conditions.
- Test flows in the console, then deploy as a hosted endpoint, cron job, or webhook-triggered workflow.
- Pair with your own agents or front-ends by calling Stack AI’s APIs, or embed their hosted UI if you want a fast launch.