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Case Study — 05
PalUp gives a sales team its own AI agent. A salesperson tells the agent who they want to reach and at what price, and the agent takes it from there — finding prospects, emailing them, and passing the lead back to a real person once someone's genuinely interested.
01 — How It Works
It starts as a conversation. The salesperson says what they need, and the agent handles the rest. It breaks the job into smaller tasks — finding the right people, building forms, sending the emails — and runs the outreach at scale, going back and forth with prospects by email. A human only steps in once a lead is actually worth their time. The same setup is built to run other kinds of agents later, for HR, marketing and beyond.

02 — Challenge
This was a product built from zero. The whole idea of an "AI sales agent" was new, and the requirements were still fuzzy when I started. There was nothing to copy from, so every screen had to be worked out from how the job would actually get done.
03 — Process
So I started from scenarios instead. I'd picture a real situation and walk through it step by step: what the user does here, what the agent does next. That told me which screens and flows the product actually needed. Doing this over and over turned a fuzzy brief into a clear structure — who can see and do what (Admin, Manager, Member), how permissions work, and how the whole system holds together as it grows. A shared design system kept it consistent as more and more screens appeared.


04 — The Product
The platform covers the whole loop a sales team runs through: setting up the team, briefing an agent, watching the tasks run, and seeing how each round of outreach did.

05 — Where It Stands
PalUp isn't an MVP yet — it's at the demo stage. The full flow, from the first brief through outreach, qualifying leads and handing them off, is designed and prototyped. The structure and design system underneath are ready to take on the next agents we have in mind, for HR and marketing.