See the layer
before you build it.
Each solution takes a real product problem, finds where AI changes behavior, and shows the before and after. These are concepts, not client wins. Every number is projected from how the workflow behaves.
Real problems, designed answers.
Pick the one closest to your product. Each shows the stuck moment, the layer we would add, and the metric it is designed to move.
- HealthcareConcept
See the sickest patients first
AI Triage Layer. The queue is blind to clinical urgency.BeforePatient reports “tiredness” and waits as Routine behind dozens of refills.With the layerDocument agent reads the CBC (hemoglobin 6.8, severely low) and the score is elevated; the patient is flagged Urgent and projected to be seen in minutes, not hours.~90%Designed to moveProjectedCritical-patient wait timeSee the full solutionconcept.uplayer.agency/patient-queue-management
- E-commerceConcept
Turn hesitation into carts
In-Product Sales Assistant. Traffic shows up. Buyers don’t.BeforeBuyer compares two similar products, gets a generic “customers also bought” carousel, and leaves.With the layerBuyer comparing products gets a side-by-side tailored to their use case (“this one has more cushion for road, that one is better if you mix road and trail”) from the assistant inline under the CTA.~2xDesigned to moveProjectedConversion rate (engaged visitors)See the full solutionconcept.uplayer.agency/ai-sales-agent-stridefit
- SaaSConcept
First API call in minutes
Integration Copilot. Developers stall before they ever make a successful call.BeforeA developer reads docs across ~180 endpoints, switches between API client and dashboard, and reaches a first successful call in roughly 20 minutes.With the layerThey describe the integration in chat; the assistant generates and previews the call, and the projected first-call time drops to a few minutes.~85%Designed to moveProjectedTime to first API callSee the full solutionconcept.uplayer.agency/ai-integration-assistant-flowsync
- SalesConcept
More replies, less grind
Outreach Intelligence. Reply rates are stuck, and the team is paying for it in time.BeforeSDRs spend ~25 minutes per prospect toggling between research, enrichment, sending, and CRM tools.With the layerResearch, draft, and strategy arrive in one view, projected time-per-prospect drops to roughly 2.5 minutes.2.6xDesigned to moveProjectedReply rateSee the full solutionconcept.uplayer.agency/automated-email-reach-out-outflow
Problem first. Metric last.
Every solution follows the path we take with a real product. You see the process before you pay for it.
- 01Find the stuck momentWhere users wait, guess, or give up inside the product.For exampleA clinic queue ordered by arrival, not by urgency.
- 02Decide where AI belongsOnly where it changes a decision. Everything else stays simple.For exampleScore severity at check in instead of adding a chatbot.
- 03Design the layer on topIt fits the workflow the team already runs, with a human in control.For exampleAn urgency panel on the dashboard doctors already use.
- 04Model the metricWe name the number and project it from how the workflow behaves.For exampleCritical patient wait time, labeled projected.
What is real and what is projected.
We would rather show our thinking than borrow someone else's results.
- RealThe problem pattern, the workflow, and the design. Each comes from how products like these behave today.
- ProjectedEvery number. We model it from the workflow and the change the layer makes, and label it projected wherever it appears.
- Not claimedNo client name, no logo, no borrowed result. When real work ships, it replaces a concept here with dated results.
The next solution here could be yours.
We take on a small number of founding partners. Real builds, real metrics, and the first results that turn these concepts into proof.
Founding program, 5 spots, 2 builds a month.
Know what you are looking at.
Are these real client projects?
No. They are concepts. Each one takes a problem pattern we see in products like it and shows how we would design the AI layer. No client is named and no result is claimed.
Where do the numbers come from?
Can you build one of these for my product?
My product is in a different industry. Does that matter?
Why show concepts instead of case studies?
Does the AI layer replace the people in these workflows?
Can I see the full thinking behind each concept?
Have a product problem? Let's talk.
Tell us what you are trying to improve and where the product is stuck. We will help you decide if an AI layer is worth building.
- NDA from the first conversation.
- Response within 24 hours, guaranteed.
- Founder-led from first call to handoff.
