Call Directory & AI Dispatch
Overview
This project focused on modernizing how critical security alerts are routed to the right people by designing a scalable call directory and evolving it into an AI-powered automated dispatch system.
The existing system relied on unstable user lists that frequently changed and disrupted escalation order. This created delays, confusion, and increased risk during high-pressure incidents.
I led the design of a centralized Call Directory system and extended it into an AI-powered automated dispatch experience, creating a unified system for intelligent incident response.
Problem
The platform’s contact management system relied on a manual, order-based call tree, which introduced major operational risks:
New users were automatically added to the top of the call order, unintentionally disrupting escalation flows
Call order dynamically changed as users were added or removed
No separation between general users and critical response contacts
Lack of prioritization led to misrouted alerts
Manual intervention was required to maintain call order
Inefficient workflows in multi-tenant and co-managed environments
This resulted in unpredictable escalation paths, delayed response times, and reduced trust in the system.
The original system relied on manual contact ordering, where newly added users were automatically placed at the top—frequently disrupting escalation workflows and introducing risk during critical incidents.
UX Research
To validate the problem and ensure the solution aligned with real-world workflows, I conducted qualitative research and usability testing with end users.
Stakeholder & User Interviews
Interviewed multiple SOC analysts and MSP administrators
Identified pain points around unstable call order and manual workarounds
Observed how teams operate during real-time incident response
Usability Testing
Conducted multiple hands-on usability testing sessions
Tested call list management, prioritization, and interaction flows
Identified friction in contact selection, ordering, and feedback
Key Insights
Users needed full control over call priority
Speed and clarity were critical during incidents
Predictable behavior was essential to build trust
Clear separation between users and escalation contacts was required
Goal
Design a system that:
Establishes a stable, prioritized call hierarchy
Separates critical contacts from general users
Enables fast, reliable escalation workflows
Scales across MSP and multi-tenant environments
Enables AI-driven automated dispatch and intelligent escalation
My Role
Lead Product Designer
Led end-to-end UX strategy and execution
Defined system architecture and interaction models
Designed scalable UI patterns and workflows
Collaborated with Product, Engineering, and SOC stakeholders
Translated business, legal, and technical constraints into UX solutions
Approach
1. System Separation
I separated the Call Directory from the User Management system to eliminate instability and create a dedicated space for prioritized contact management.
This ensured predictable system behavior and created the foundation required for automation.
A dedicated Call Directory was introduced with a guided empty state, allowing teams to build structured, prioritized contact lists independent of user management.
2. Structured Call Hierarchy
I designed a priority-driven contact system that gives teams full control over escalation order:
Explicit ordering of contacts
Drag-and-drop prioritization
Controlled list size for escalation
Support for internal and external contacts
This allowed teams to define exactly who should be contacted and in what order, eliminating ambiguity during critical incidents.
3. Scalable Contact Management
I designed complete interaction flows to support real-world contact management at scale:
Search and quickly add contacts from existing users
Add and manage external contacts
Bulk selection and batch actions
Conflict handling and validation states
First-time setup and ongoing management
These workflows ensured consistency, accuracy, and reduced manual effort across environments.
Search-driven workflows enable teams to quickly find and add contacts, streamlining contact management and reducing manual effort across large datasets.
4. Feedback & System Clarity
I introduced standardized feedback patterns:
Toast messaging for success and error states
Undo actions for destructive changes
Clear, concise system responses
This improved usability and reduced confusion during critical workflows.
5. Enterprise-Ready UX
The system was designed for:
MSP administrators managing multiple tenants
SOC analysts operating in high-pressure environments
Co-managed customer scenarios
It supports clear workflows, predictable behavior, and reduced cognitive load during incidents.
Solution
The Call Directory delivers:
Centralized, prioritized contact directory
Stable escalation order with no auto-reordering
Drag-and-drop priority management
Internal and external contact support
Fast, action-oriented workflows
Seamless platform integration
Impact
Eliminated unstable call hierarchy issues
Reduced time to identify correct contacts
Improved incident response efficiency
Increased usability across teams
Enabled AI-driven automateddispatch and improved escalation efficiency
Phase 2: AI Automated Dispatch
Overview
As part of this system, I designed an AI-powered automated dispatch experience to streamline communication during critical incidents.
The system automates outbound calls by identifying the right contacts, generating contextual messaging, and initiating communication without manual intervention.
AI-Powered Dispatch & Real-Time Escalation
AI-powered dispatch routes alerts, tracks outcomes, and escalates incidents in real time.
The AI-powered dispatch system introduces real-time automation into incident response workflows:
Automatically routes alerts to prioritized contacts
Tracks outcomes (Connected, Voicemail, No Answer)
Dynamically escalates when contacts are unreachable
Enables fast, reliable response during critical events
Why This Matters
Without a structured Call Directory:
Contact prioritization becomes unreliable
Escalation workflows break down
Automation introduces risk instead of efficiency
The Call Directory acts as the foundation that enables AI to make accurate, reliable decisions.
AI System Design
The AI dispatch system is powered by a unified architecture that transforms a static contact list into an intelligent, real-time escalation engine.
At its core:
Call Directory as the single source of truth
A structured, priority-driven contact system ensures consistent and reliable escalation paths across all incidents.Automated routing logic
Alerts are dynamically routed based on severity, contact priority, and availability—removing the need for manual intervention.AI-generated messaging
Context-aware notifications are generated based on incident type, enabling faster understanding and response by recipients.Real-time escalation engine
The system continuously evaluates outcomes (Connected, Voicemail, No Answer) and automatically escalates to the next contact when needed.
This architecture shifts incident response from a manual, error-prone workflow to a scalable, intelligent system capable of handling real-world operational complexity.
Key Capabilities
Automated outbound calls during incidents
AI-generated summaries for call messaging
Role-based contact selection
Escalation workflows if contacts do not respond
User interaction to connect with SOC
UX Challenges Solved
Trust & Transparency
Designed clear visibility into AI decisions so users understand who is being contacted and why.
Configuration Complexity
Created intuitive controls for enabling, configuring, and managing automated dispatch.
Legal & Compliance
Designed opt-in and opt-out experiences to support consent, auditing, and regional requirements.
My Role
Designed AI-assisted workflows and interaction models
Defined system logic and user controls
Created UX for configuration, activation, and monitoring
Collaborated across Product, Engineering, and Legal
Status
Call Directory: Complete and deployed
AI Automated Dispatch: Designed and nearing implementation
Final Takeaway
This project demonstrates my ability to design systems that evolve from manual workflows into intelligent automation.
I didn’t just design a feature—I designed a scalable system that enables AI-driven operations in complex enterprise environments.