Services · Core offer
AI that people actually want to use
Capable AI still fails when people won't use it. Palmetto designs the experience around the agent: how it shows its work, how it asks for approval, and how complex information gets presented so it lands. We prototype in working software, so you can put something real in front of real users early.
01 · When to call
Start with the condition you can observe, the consequence it creates, and the person accountable for changing it.
The model tested well, but adoption stalled once real users got it
People copy agent output into another tool because they can't see where it came from or what it did
Leaders get dashboards and reports full of data, and the decision still takes a meeting to explain
Several teams are about to build AI features, and each one would invent its own interface patterns
02 · Where it shows up
We apply these patterns to the workflow, systems, decision rights, and measures that drive your business.
Show what the agent did, what it used, and what it wants to do next. Approvals, corrections, and handoffs sit where the person is already working.
Turn complex information into a view someone can read and act on: what changed, why it matters, and what needs a decision.
Learn the real job, map the workflow, and design the screens and the conversation together, including what happens when the AI is unsure or wrong.
Build a shared set of components and patterns, then prototype in working software on representative data so users react to something real.
03 · The work product
Core deliverables
Production and governance controls
04 · Delivery path
We start with one workflow and the people who use it, test a working prototype, then carry the design into the product.
01
Define the business problem, baseline the current state, test feasibility, and make the value, risk, and decision path explicit.
Typical output
Decision brief, baseline, target state, and sequenced recommendations
02
Test the hardest assumptions with representative data, real users, an interface they can work in, appropriate controls, and an architecture that can survive past a demo.
Typical output
Working pilot, evaluation evidence, operating lessons, and go-forward decision
03
Harden what works, integrate it into the operating environment, expand adoption, and transfer the knowledge required to run and improve it.
Typical output
Production capability, rollout evidence, runbooks, and ownership handoff
05 · Measures & team
Measures that show progress
The team we build with
06 · Ownership
Designs, the design system, prototype code, and research findings are documented and handed to your team.
07 · Questions buyers ask
Its output changes, and sometimes it's wrong. People need to see what the agent used, correct it, and know when to step in. That design work decides whether anyone keeps using the product.
Start with this site. Palmetto designed and built it. Sweetgrass, one of our open-source projects, is a visual planning surface for agent-driven projects. The better test is a working prototype on your own workflow, and we can scope one early.
Yes. We can lead the design work, pair with your designers, or build on a design system you already have.
09 · Start with the business problem
Share the workflow or decision, who owns it, what it costs today, and what makes the timing matter. We turn that context into a practical path with clear deliverables, measures, timing, and commercial terms.
Discuss an AI experience →Or email support@palmettointeractive.com.
