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UX & Product Engineering

Designing experiences that drive adoption — research-led UX, product thinking, design systems, and interaction patterns for web, mobile, data products, and AI-first interfaces.

Talk to our UX team View case studies

Who this CoE is for

Workflow-heavy application teams

Products where usability directly determines whether users adopt the system or work around it.

Interface modernization programs

Organizations replacing legacy interfaces and user journeys without losing operational continuity.

Products scaling design systems

Teams that need design consistency and delivery speed across multiple products or squads.

AI and data platform teams

Interfaces that must make complex AI behavior clear, trustworthy, and controllable for real users.

What this CoE helps you achieve

Higher adoption

Workflows that match how people actually work — reducing friction and the need for workarounds.

Clearer operations

Interfaces that reduce errors and support real operational tasks, not just polished demos.

Reusable systems

Design systems and component libraries that accelerate delivery across teams and products.

Trustworthy AI experiences

AI and data interfaces with clear controls, explainability, and graceful failure modes.

What this CoE focuses on

Building product experiences that are usable, consistent, and scalable.

Low adoption due to complex workflows and poor information architecture

Inconsistent UI patterns across teams and products

Legacy interfaces that are difficult to modernize safely

Data products that are hard to interpret or trust

AI experiences that need transparency, control, and clear failure modes

Accessibility and inclusive design requirements

Why it matters

Great engineering fails if users cannot adopt the system.

Adoption

How do you design workflows that match how people actually work?

Consistency

How do you scale design across teams without fragmentation?

Trust

How do you make data and AI systems explainable and controllable?

Accessibility

How do you ensure inclusive experiences and compliance-ready design?

BeeHyv treats UX as an engineering capability — embedded into squads, measurable, and designed for scale.

Engineering Frameworks

Three frameworks that drive consistent, adopted UX across every engagement.

Research & Discovery

User research and workflow mapping

Capabilities

Assets

User research & interview frameworks
Workflow mapping & task analysis
Information architecture
Research templates
Journey mapping tools

Design Systems

Component libraries and pattern documentation at scale.

Capabilities

Assets

Component libraries with documentation
Cross-team consistency patterns
Theming and customization frameworks
Accessibility compliance (WCAG)
Figma/Storybook integration
Pattern documentation templates
Design token systems

AI Interface Patterns

Making AI trustworthy and controllable for users.

Capabilities

Assets

Confidence indicators & explainability
Feedback loops & correction flows
Progressive disclosure for complex AI
Error handling & graceful degradation
AI transparency patterns
Human-in-the-loop UI patterns
Trust signal frameworks

How we deliver

UX Designers

Research, wireframing, design systems

Frontend Engineers

React, Flutter, responsive implementation

Product Manager

Requirements, prioritization, user feedback

Technology Stack

Representative work

Case Studies

800K+ farmers

Digital Agriculture Platform

Multi-lingual web and mobile interfaces.

  • First in India
  • React + Flutter
  • Role-based dashboards

Zero downtime

Payment Admin Platform

Legacy Struts → React SPA with BFF layer.

  • Self-serve reduced eng intervention
  • Rollback-safe deployments
  • Azure AD B2C auth

Zero downtime

3-week rollout

Healthcare Audit Portal

State-wide portal with offline mobile geo-tagged audits.

  • Hours → minutes resolution
  • 18,000+ hospital network
  • Medical code normalization

Ready to build?

Ship AI that works
at production scale.

From prototype to production. From platform to population scale.

Talk to our team See case studies