Case Study: Inform
Reimagining the Modern SOC
Multi-Monitor Experience
Inform automates Security Operations Centers. It uses AI to monitor & triage all threats simultaneously in real time, and automate your responses, saving operator time, responding faster, and reducing false alarms. AI-driven, connected experiences that seamlessly link people, devices, and data intelligence across platforms.
Custom Native Mobile App
A native mobile app tailored for managers and supervisors, giving them instant access to live video feeds, alerts, and camera health insights while on the move. It enabled them to review incidents, verify system status, and respond to security events in real time, with localization built in to support users across different regions and languages.
The Challenge
At Motorola Solutions, we identified a critical challenge in Security Operations Centers (SOCs): operators were overwhelmed by fragmented alerts, disjointed systems, and constant context switching—leading to fatigue, errors, and missed incidents. SOC managers faced high turnover, compliance pressures, and limited visibility into performance.
Despite having strong individual products—Avigilon Unity, DMS, and Facility/SOC tools—there was no unified experience connecting them. This initiative aimed to close that gap by designing an integrated SOC platform that reduces noise, enhances situational awareness, and unifies Motorola’s ecosystem into a cohesive, operator-first experience.
My Role
As Director of UX, I led the end-to-end design strategy for Inform—Motorola’s next-generation SOC platform—unifying previously siloed products (Avigilon Unity, DMS, Facility) into a cohesive, operator-centered experience. I managed a global team of designers, researchers, and prototypers across Chicago, Vancouver, Lisbon, and Bangkok, partnering with Product, Engineering, and AI leadership to align research, roadmap priorities, and design investments in workflows, multi-modal interfaces, and alert triage.
Primary Personas
Integrators / Installers, Security Operators, Security Operator Managers
Approach
Evaluating AI options
What Are MSI’s AI Camera Systems Capabilities?
AI Camera Systems are video surveillance solutions equipped with advanced artificial intelligence algorithms that can detect, analyze, and respond to various events in real-time. These systems rely on machine learning, computer vision, and sometimes deep learning models to identify objects, faces, or behaviors, enhancing security and operational decision-making.
Why Use AI Camera Systems?
AI Camera Systems at MSI can boost security, improve operational efficiency, and minimize human errors. By automating tasks like motion detection and object recognition, these systems enable fast responses to incidents and offer valuable data-driven insights for better resource allocation and loss prevention.
What Are MSI’s Limitations of AI in Video Surveillance?
While AI Camera Systems offer promising capabilities, challenges include potential biases in facial recognition algorithms, privacy concerns, and reliance on stable network infrastructure. Additionally, integration with legacy systems can pose technical and budgetary hurdles.
What Are The Key Features of AI Camera Systems?
There are three tiers of AI offerings to decipher between:
Tier 1: Motion, people, and vehicle detection
Tier 2: License plate recognition
Tier 3: AI assistants, universal search, and action detection
Foundational Research
We began with immersive foundational research, visiting real SOCs across North America—including Georgia Tech Police, Coca-Cola, and Cox Communications—to map current workflows, tools, and mental models of the Operator, Manager, and Admin personas.
Top Use Cases for AI Camera Systems by Verticals
Manufacturing and Logistics
Ensuring worker safety, streamlining operations, tracking shipping processes.
Education and Campus Security
Identifying unauthorized access, monitoring perimeters, ensuring student safety.
Law Enforcement
Assisting in suspect identification, searching historical videos, managing evidence.
Retail and Hospitality
Monitoring foot traffic, improving customer experiences, deterring theft.
Design Thinking Workshops & Roadmap
To establish a shared understanding of our product’s personality, I initiated and led a series of cross-functional ideation sessions with Design, Product, and Engineering teams. Each session was structured to ensure balanced participation and alignment across disciplines.
Through guided exercises and discussions, we explored how teams currently perceived the product and where they envisioned its evolution. I synthesized the collective insights, affinity mapped themes.
Affinity mapping helped us cluster those insights into themes like:
System Fragmentation: “I have to log in to five different tools.”
Alert Fatigue: “There are too many notifications — I tune them out.”
Training Gaps: “We don’t know what half these features do.”
Workflow Interruptions: “Switching between screens breaks my focus.”
Trust in AI: “I’m not sure if I can rely on these alerts.”
Then distilled them into a clear set of foundational product principles to guide future design and development decisions:
Clarity Over Complexity – Surface only what’s relevant; reduce visual and cognitive noise in high-stress environments.
Actionable Intelligence – Data is only useful if it drives timely, confident action.
Unified Experience – Users shouldn’t feel the seams between products; the ecosystem must feel like one system.
Trust Through Transparency – Make AI decisions explainable; operators should understand why an alert was triggered.
Designed for Focus – Prioritize calm, legible interfaces that support decision-making under pressure.
Accessible by Default – Ensure every operator, regardless of skill or background, can succeed without heavy training.
These principles were documented and shared broadly, ensuring visibility, alignment, and consistency across the organization as we scaled the system.
We jumped right into prototyping, kicking things off with rapid Figma layouts to bring early concepts to life.
I championed a modular design system and AI-first framework for our integrated SOC platform, introducing:
Smart Tours: AI-curated camera sequences for proactive monitoring. Leveraged MCAP AI for real-time scene recognition and intelligent alert filtering - differentiating between benign actions
Contextual Alert Summaries: Natural language descriptions, tied to FOA maps and historical device activity
Multi-modal Dashboards: Role-based layouts for operators, supervisors, and incident investigators
Cross-Product Integration: Unified workflows connecting Avigilon Unity (video), Facility (alerts), and access control. Introduced single sign-on (SSO) across Motorola platforms—consolidating databases and permissions by persona (operator, supervisor, investigator).
Single Design System: Established a shared design system to unify UI patterns, workflows, and accessibility standards across cloud and on-prem
Once the roadmap was in place, we broke it down into feature streams and assigned them to the respective development teams. The design team worked closely throughout the process — from feature design to handoff and go-live — collaborating with cross-functional partners and refining along the way as needed.
Throughout the process, we prototyped rapidly in Figma and iterated based on field/user feedback, integrating input from early pilot customers and Motorola’s internal security teams.
Outcomes
The Inform SOC platform prototype brought clarity and cohesion to what had previously been a fragmented operator experience. Our AI-powered alert summaries, FOA map integration, and Smart Tour workflows were met with strong validation from both internal and external stakeholders:
40% reduction in time to verify incidents (measured in internal SOC pilot vs legacy flow)
2x increase in situational clarity among operators during scenario testing (based on qualitative usability sessions)
Decreased false alarm fatigue by integrating Smart Filtering logic and scene-aware camera summaries
Accelerated product alignment and development by 40% across Avigilon Unity, Facility, and DMS teams, establishing a unified roadmap and shared design system
Influenced roadmap priorities and sales demos for enterprise clients in education, healthcare, and law enforcement verticals
The platform also helped shift Motorola’s internal conversation from feature gaps to workflow unification - bringing design, product and engineering stakeholders into shared ownership of the operator experience.
Reflection
Leading this effort reinforced my belief that alignment is design's most powerful multiplier. Getting product, engineering, and go-to-market teams to co-own the operator journey unlocked better decisions and greater velocity.
I also learned the value of designing for resilience and clarity in high-stress environments. Security operators don’t need more data—they need better defaults, clear prioritization, and role-aware tools that guide rather than overwhelm. Much of my role was not just in designing interfaces, but in creating shared understanding around what problems we were truly solving and for whom.
If I were to do this again, I would push even earlier for cross-functional prototyping with real client data—and extend our validation cycles deeper into post-incident review workflows to close the loop on SOC accountability.
