Many teams start with AI as a chatbot. It’s visible, easy to test, and feels powerful, but in day-to-day operations, it’s often not where the real value comes from
AI chatbot
- Requires users to ask questions
- Lives outside existing workflows
- Useful for exploration and quick answers
AI inside workflows
- Works automatically in the background
- Enhances existing systems
- Supports real actions: tagging, routing, prioritization
Chatbots can be helpful, but they depend on user interaction. Embedded AI reduces manual work without changing how teams operate
What does practical, agentic AI look like in a real business workflow?
Our new TechFoundry IMS case study walks through seven demos—from purchase-order intake and catalog conflict resolution to vendor orders, shipments, client shipping, and invoice reconciliation.
It shows how AI agents, document processing, and software integrations work together, with human review where judgment matters. I’ve also included the technology stack behind the platform.
Purchase-order intake and catalog conflict resolution feel like the right place to start with agents, since the pain is concrete. How do you handle the cases where the agent is unsure and a human has to step in?
Feels like a lot of companies are trying their luck with AI instead of hiring designers right now.
I think it's going to backfire on them in a few months.
Trying to stay optimistic about it.
A 60-second promo for Ulta AI by Ultahost, a chatbot that runs a server through plain conversation. Script, storyboard and animation, all built around the real product UI.