Key Achievements
Unified Conversational Support Experience
Created Intel's first unified AI assistant, replacing fragmented support pathways with guided conversational interface that improves task discovery.
Enterprise-Ready Conversational Architecture
Designed scalable conversational framework with reusable chat patterns, escalation logic and message structures for consistent AI experiences.
Frictionless Task Completion
Streamlined complex troubleshooting flows into clear, step-by-step conversational paths, reducing confusion and improving task completion.
Key Achievements
Unified Conversational Support Experience
Created Intel's first unified AI assistant, replacing fragmented support pathways with guided conversational interface that improves task discovery.
Enterprise-Ready Conversational Architecture
Designed scalable conversational framework with reusable chat patterns, escalation logic and message structures for consistent AI experiences.
Frictionless Task Completion
Streamlined complex troubleshooting flows into clear, step-by-step conversational paths, reducing confusion and improving task completion.
Key Achievements
Unified Conversational Support Experience
Created Intel's first unified AI assistant, replacing fragmented support pathways with guided conversational interface that improves task discovery.
Enterprise-Ready Conversational Architecture
Designed scalable conversational framework with reusable chat patterns, escalation logic and message structures for consistent AI experiences.
Frictionless Task Completion
Streamlined complex troubleshooting flows into clear, step-by-step conversational paths, reducing confusion and improving task completion.
Key Achievements
Unified Conversational Support Experience
Created Intel's first unified AI assistant, replacing fragmented support pathways with guided conversational interface that improves task discovery.
Enterprise-Ready Conversational Architecture
Designed scalable conversational framework with reusable chat patterns, escalation logic and message structures for consistent AI experiences.
Frictionless Task Completion
Streamlined complex troubleshooting flows into clear, step-by-step conversational paths, reducing confusion and improving task completion.
Context
Intel had no unified AI support experience. Customers bounced between documentation, forums and contact forms trying to find answers to common technical questions. The support ecosystem was fragmented across multiple disconnected systems. Each business unit had different approaches to helping users.
Role & Scope
I led the end-to-end design of Ask Intel, the company's first enterprise-wide conversational assistant. This meant defining the conversational model, building the chat UI and creating a scalable component system. This was a ground-up effort. No prior assistant, no existing framework, no shared model for conversational behavior. I established the foundation that Intel's conversational experiences continue to scale on.
Role
Senior Product Designer, Design Systems Lead for Digital Experiences at Intel
Platform
Web (responsive), integrated across Intel.com support ecosystem
Collaboration
Support teams, content owners, engineering, NLP teams
Role & Scope
I led the end-to-end design of Ask Intel, the company's first enterprise-wide conversational assistant. This meant defining the conversational model, building the chat UI and creating a scalable component system. This was a ground-up effort. No prior assistant, no existing framework, no shared model for conversational behavior. I established the foundation that Intel's conversational experiences continue to scale on.
Role
Senior Product Designer, Design Systems Lead for Digital Experiences at Intel
Platform
Web (responsive), integrated across Intel.com support ecosystem
Collaboration
Support teams, content owners, engineering, NLP teams
Role & Scope
I led the end-to-end design of Ask Intel, the company's first enterprise-wide conversational assistant. This meant defining the conversational model, building the chat UI and creating a scalable component system. This was a ground-up effort. No prior assistant, no existing framework, no shared model for conversational behavior. I established the foundation that Intel's conversational experiences continue to scale on.
Role
Senior Product Designer, Design Systems Lead for Digital Experiences at Intel
Platform
Web (responsive), integrated across Intel.com support ecosystem
Collaboration
Support teams, content owners, engineering, NLP teams
Role & Scope
I led the end-to-end design of Ask Intel, the company's first enterprise-wide conversational assistant. This meant defining the conversational model, building the chat UI and creating a scalable component system. This was a ground-up effort. No prior assistant, no existing framework, no shared model for conversational behavior. I established the foundation that Intel's conversational experiences continue to scale on.
Role
Senior Product Designer, Design Systems Lead for Digital Experiences at Intel
Platform
Web (responsive), integrated across Intel.com support ecosystem
Collaboration
Support teams, content owners, engineering, NLP teams
Design Constraints
Fragmented support pathways
Users navigated multiple disconnected systems. Product pages, docs, forums and contact forms all existed separately. Finding basic answers required jumping between them.
Long wait times for simple queries
Live support agents spent significant time on repetitive questions that could be automated. This created bottlenecks for users with complex issues.
Poor mobile experience
Technical documentation wasn't optimized for mobile. Yet many users troubleshooted on phones while working with their hardware.
No intelligent triage
There was no system to guide users to the right information based on their specific needs and context. Everyone got the same generic starting point.
Design Constraints
Fragmented support pathways
Users navigated multiple disconnected systems. Product pages, docs, forums and contact forms all existed separately. Finding basic answers required jumping between them.
Long wait times for simple queries
Live support agents spent significant time on repetitive questions that could be automated. This created bottlenecks for users with complex issues.
Poor mobile experience
Technical documentation wasn't optimized for mobile. Yet many users troubleshooted on phones while working with their hardware.
No intelligent triage
There was no system to guide users to the right information based on their specific needs and context. Everyone got the same generic starting point.
Design Constraints
Fragmented support pathways
Users navigated multiple disconnected systems. Product pages, docs, forums and contact forms all existed separately. Finding basic answers required jumping between them.
Long wait times for simple queries
Live support agents spent significant time on repetitive questions that could be automated. This created bottlenecks for users with complex issues.
Poor mobile experience
Technical documentation wasn't optimized for mobile. Yet many users troubleshooted on phones while working with their hardware.
No intelligent triage
There was no system to guide users to the right information based on their specific needs and context. Everyone got the same generic starting point.
My Approach
Action-Driven Discovery
Analyzed support ticket data to identify the top 20 most common user questions. Interviewed customer support teams to understand pain points and escalation patterns. This revealed which questions could be automated and which required human expertise.
Action-Driven Discovery
Analyzed support ticket data to identify the top 20 most common user questions. Interviewed customer support teams to understand pain points and escalation patterns. This revealed which questions could be automated and which required human expertise.
Conversation as Guided Navigation
Designed conversation flows using topic-based navigation with quick-reply buttons rather than open-ended text input. This reduced cognitive load and improved task success. Users didn't have to phrase questions perfectly. They could navigate by selecting relevant topics.
Conversation as Guided Navigation
Designed conversation flows using topic-based navigation with quick-reply buttons rather than open-ended text input. This reduced cognitive load and improved task success. Users didn't have to phrase questions perfectly. They could navigate by selecting relevant topics.
Transparency by Design
Surfaced data usage disclaimers upfront. Designed clear escalation paths to human agents when AI couldn't help. Users always knew when they were talking to a bot versus being transferred to a person.
Transparency by Design
Surfaced data usage disclaimers upfront. Designed clear escalation paths to human agents when AI couldn't help. Users always knew when they were talking to a bot versus being transferred to a person.
Design System Integration
Built every component using Intel's Atomic Design System. This ensured visual consistency and WCAG 2.1 AA accessibility from day one. Contributed conversational components back to the system so future teams could reuse them.
Design System Integration
Built every component using Intel's Atomic Design System. This ensured visual consistency and WCAG 2.1 AA accessibility from day one. Contributed conversational components back to the system so future teams could reuse them.
Detailed Results
Key Takeaways for the Future
When systems break, teams slow down.
I work across UX, architecture and content to prevent fragmentation and help organizations move faster with confidence.
My Approach
Action-Driven Discovery
Analyzed support ticket data to identify the top 20 most common user questions. Interviewed customer support teams to understand pain points and escalation patterns. This revealed which questions could be automated and which required human expertise.
Conversation as Guided Navigation
Designed conversation flows using topic-based navigation with quick-reply buttons rather than open-ended text input. This reduced cognitive load and improved task success. Users didn't have to phrase questions perfectly. They could navigate by selecting relevant topics.
Transparency by Design
Surfaced data usage disclaimers upfront. Designed clear escalation paths to human agents when AI couldn't help. Users always knew when they were talking to a bot versus being transferred to a person.
Design System Integration
Built every component using Intel's Atomic Design System. This ensured visual consistency and WCAG 2.1 AA accessibility from day one. Contributed conversational components back to the system so future teams could reuse them.
Key Takeaways for the Future
Context
Intel had no unified AI support experience. Customers bounced between documentation, forums and contact forms trying to find answers to common technical questions. The support ecosystem was fragmented across multiple disconnected systems. Each business unit had different approaches to helping users.
Detailed Results