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Ulaş AlyeşilProduct designer · Istanbul
All work

WiseCareAIMarket-ready product · not launched

WiseCareAI

Role
Founding Product Designer
Timeline
May 2024 — August 2025
Team
Founding team
Platforms
Agent tools, internal operations, and public web

WiseCareAI is a health-insurance platform for the U.S. market. As founding product designer, I shaped the product language, information architecture, core flows, and shared system across agent tools, internal operations, and the public site. Generative UI/AI supported core workflows rather than replacing them.

WiseCareAI overview cover

Product scope:

  • ACA Enrollment (Agent): guided quoting/enrollment with dynamic form blocks.
  • Medicare Quoting (Phone): quick compare with rationale for seniors.
  • Internal Ops (CRM): timeline/status insights from notes and events.
  • Marketing Site: clear story and trust signals in a regulated domain.
  • Design System: tokens, components, patterns (including generative states).

My contribution:

  • Information architecture and navigation across tools.
  • Wireframes → hi-fi UI → prototypes; dev handoff.
  • Design system definition and maintenance.
  • AI feature integration: prompts/guardrails/UX for explainability and edits.
Dynamic form block example

Where AI/Generative fits (as augmentation):

  • Adaptive steps/fields when case context changes.
  • Free-form intent or guided inputs—both converge to the same editable draft.
  • Rationale overlays: why a plan is suggested (cost, coverage fit, eligibility).
  • Recovery loops: quick fixes to model mistakes without losing progress.

Key design challenges:

  • Stability vs plasticity: keep anchors while the work area adapts.
  • Trust without overload: show a one-glance rationale; expand for trace.
  • Preview vs commit: drafts first; explicit, reversible writes.
  • Policy complexity: ACA/Medicare rules without exposing regulation-speak.

Pattern: Anchor Layout — persistent navigation/header/progress; only the canvas mutates. Reduces disorientation while supporting flexible steps.

Enrollment flow with stable anchors

Pattern: Preview → Refine → Commit — AI creates drafts (plans/forms/messages). Agents adjust inline chips (filters/constraints) before any system write.

Plan compare draft
Plan refine and commit

Explainability surface: compact rationale (cost, fit, eligibility) with tap-to-expand trace to sources and constraints.

Explainable selection wizard

Interaction modes: free-form need statements or guided steps. Users can switch modes any time; both routes land on the same draft.

AI result with rationale chips
Agent thinking / drafting state

System behavior (with engineering): prompt scaffolds, eligibility guardrails, deterministic anchors, streaming feedback, error classes mapped to recovery UI.

Patterns distilled:

  • Correction Loop — inline edits update the draft and current context.
  • Anchor Layout — stable shell; generative canvas.
  • Preview-First — drafts by default; explicit commit.
  • Rationale Card — concise “why”, expandable trace.
  • Low↔High Agency Toggle — guided steps or free-form intent.
  • Memory Notes — lightweight notes the agent and system can reference.

Delivery stage: the product was brought to a market-ready state, but it was not launched. This page describes the designed and delivered capability, not measured customer outcomes or a completed acquisition.

Marketing: straightforward, credible narrative; visuals aligned with product explainability and regulation sensitivity.

Public marketing site

The resulting product gave the team a consistent foundation for agent workflows, internal operations, and public-facing communication, with drafts and review states where generative assistance was involved.