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Frontend · Backend

Платформа сравнения медицинской страховки

Умный сравниватель планов медицинского страхования.

КлиентMy Coverage PlanОтрасльHealthcareДлительность16 weeksКоманда1 PM, 3 engineers, 1 designerСтек
  • Angular
  • Node.js
  • Payload CMS
  • PostgreSQL
  • AWS
  • Stripe
01

Вызов

Users needed simple way to explore and compare healthcare insurance plans to find coverage matching their specific needs.

02

Наш Подход

Built personalized platform with Angular and Node.js using Payload CMS, delivering seamless comparison experience on AWS.

03

Результаты

  • Personalized plan recommendations
  • Seamless comparison experience
  • Secure AWS deployment
  • User-friendly interface for smarter coverage decisions

How we delivered it

Every case study on this site follows the same delivery spine — the four-phase process we have refined across fifty-plus production engagements.

01 · 1–2 weeks

Discovery & Strategy

Stakeholder interviews, technical audit, success metrics, phased roadmap.

02 · 2–4 weeks

Design & Prototyping

User research, design systems, interactive prototypes approved before code.

03 · 4–16 weeks

Development & QA

Two-week sprints, weekly demos, automated testing, continuous deployment.

04 · Ongoing

Launch & Scale

Production rollout, observability, incident response, feature evolution.

Why ConfiaTech for projects like this

Senior engineers, end to end

Every contributor on the engagement had at least five years of production experience. No learning on the client dime.

KPI-anchored delivery

Outcomes — not deliverables — drive the roadmap. Weekly demos report progress against the metric, not against the backlog.

Runbooks before launch

Production observability, incident playbooks, and handoff documentation ship with every release.

Continuity past launch

The same engineers who built the product support and evolve it. Institutional knowledge stays inside the engagement.

Have a similar project in mind?

Walk us through your problem. Within one business day a senior engineer will recommend the engagement model, team composition, and timeline that maps closest to this case study.

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