Designing an
AI-Powered Identity Security Platform
Enterprise SaaS ▫️ AI Product Design ▫️ Security UX ▫️ Governance & Compliance ▫️ Complex Workflows ▫️ Stakeholder Alignment
PROJECT OVERVIEW
ObserveID is an AI-powered identity security platform that brings IAM, IGA, PAM, CIEM, and threat detection into one unified experience.
As the founding and only product designer, I owned the end-to-end product experience across complex security workflows, from information architecture and dashboards to AI-powered experiences and the design system. I also introduced AI into my own design process to accelerate exploration, synthesis, and iteration while maintaining human-led UX judgment.
COMPANY
ObserveID
ROLE
Founding Product Designer
TIMEFRAME
16 months
TECH-STACK
Figma (design + system library), GitHub (version control), FigJam (workshop & ideation), Jira/Confluence (handoff)
THE CHALLENGE
Identity security is complex: enterprises struggle with limited visibility into access across hybrid and multi-cloud environments, fragmented tools that create disjointed workflows, manual compliance and audit processes, and high-risk analysis requiring deep technical expertise. ObserveID needed to unify these challenges into clear, actionable, and enterprise-ready experiences.
Additionally, as the first designer, there was no existing design language, UX process, or shared system, meaning a foundational structure had to be built.
MY APPROACH
I unified fragmented identity security workflows into a single operational experience while designing new interaction models for AI-assisted security analysis.
The work spanned information architecture, risk visualization, dashboards, workflow design, conversational AI, enterprise customization, and a scalable design system. Alongside designing AI-powered product experiences, I used AI throughout my own workflow for ideation, synthesis, exploration, and iteration.
STEP 1
DEFINE
UNDERSTANDING THE PROBLEM
Defined the core UX challenges by understanding stakeholder needs and evaluating the existing product experience.
ENGAGING STAKEHOLDERS
Spoke with founders, product, engineering, and customer success to understand business priorities, customer pain points, and operational needs.
Key focus: workflow bottlenecks, compliance needs, and enterprise customization requirements
AUDITING THE EXISTING SYSTEM
Reviewed existing dashboards and workflows across IAM, IGA, PAM, and CIEM.
Identified fragmented workflows, inconsistent UI patterns, data overload, and limited opportunities for AI-assisted insights.
STEP 2
IDEATE
TURN FINDINGS INTO POSSIBLE SOLUTIONS
Explored different ways to simplify complex security workflows, improve information hierarchy, and introduce AI where it could meaningfully support users.
BRAINSTORMING SESSIONS
Combined human and AI brainstorming to explore workflow improvements, interaction patterns, and opportunities for AI-assisted experiences.
WORKFLOW EXPLORATION
Explored potential workflows and translated promising ideas into quick hand sketches to work through the experience before moving into digital design.
AI EXPLORATION & VALIDATION
Used AI to explore and visualize directions from the initial sketches, then shared the concepts with stakeholders to refine and validate the approach before wireframing.
STEP 3
DESIGN
CREATING THE SOLUTION
Designed high-fidelity interfaces, dashboards, and workflows to make enterprise identity security intuitive, actionable, and consistent.
DASHBOARD & ANALYTICS
Multi-pane dashboards combining risk insights, entity details, and alerts
AI-assisted, explainable analytics to guide decision-making
Real-time data visualizations with actionable drill-downs
WORKFLOWS & INTERACTION PATTERNS
Unified access certification, lifecycle automation, and compliance flows
Streamlined navigation connecting dashboards, actions, and reports
Consistent UI patterns across repetitive workflows to reduce cognitive load
OBI: CONVERSATIONAL UI
Designed AI-assisted conversational interfaces to help users query, explore, and act on identity data
Embedded natural language prompts for guided workflows
Integrated risk explanations and remediation suggestions within the conversation flow
AI DESIGN PRINCIPLES
Context over answers
AI surfaced relevant identity and risk context rather than presenting unexplained conclusions.
Explain before action
Users could understand why a risk was identified before acting on an AI recommendation.
Human in the loop
AI supported investigation and decision-making while keeping consequential actions under user control.
CUSTOMIZATION & ENTERPRISE BRANDING
Allowed enterprise clients like Warner Bros. to personalize dashboards (colors, logos, layouts)
Flexible widget placement and configuration to meet different operational needs
DESIGN SYSTEM
Built an atomic design system with reusable tokens, components, and patterns, documenting usage, states, and version control for engineering adoption, while maintaining interface consistency and enabling rapid iteration across modules.
STEP 4
DESIGN TO DEV
BRINGING THE SOLUTION INTO PRODUCTION
Prepared production-ready specifications, components, and workflows to enable engineering teams to implement the platform accurately and consistently at scale.
IMPLEMENTATION ALIGNMENT
Delivered annotated specs with interaction states, error cases, and data conditions to guide engineering
Synced Figma components and design tokens with code for 1:1 implementation and consistency
Maintained semantic versioning and documented usage to reduce ambiguity and enable rapid iteration
Collaborated with engineering and supported enterprise onboarding
KEY LEARNINGS
Designing for complex workflows matters — Streamlined IAM, IGA, PAM, and CIEM modules to reduce cognitive load and simplify actions.
Design systems drive consistency — Built an atomic design system adopted by engineering for scalable, repeatable interfaces.
Explainable AI builds trust — Integrated AI-assisted conversational UI with clear guidance and actionable insights.
Collaboration ensures implementation — Close alignment with engineering and enterprise clients enabled smooth rollouts.
THE IMPACT
Warner Bros. onboarded ObserveID because the platform solved a unique use case that existing tools couldn’t address
Enterprise clients adopted unified dashboards which simplified risk analysis and compliance workflows for security teams
Design system reduced development ambiguity and accelerated handoff and iteration across modules
Workflows and AI interfaces increased operational efficiency allowing teams to act faster and more confidently on identity risks
CONCLUSION
Working on ObserveID deepened my skills in designing for complex enterprise workflows, scalable systems, and AI-assisted interfaces.
