Case Study · 03 — Prevalent AI

Exposure
Management
Platform

A unified exposure view across assets, controls, and attack surface — shifting analysts from siloed risk assessments to a connected, knowledge-graph-powered understanding of their environment.

Enterprise UX Cybersecurity Data Visualization Knowledge Graph Dec 2024 – Jan 2025 · 8 Weeks · Design Lead
Exposure Management Platform — dashboard on monitor

The platform brings together cloud controls, external attack surface data, and internal asset context through a shared knowledge graph to present exposure as a connected system rather than isolated findings.

Design focuses on helping users navigate relationships, dependencies, and impact, enabling clearer understanding and prioritization across complex security environments.

User Focus
Security / SOC Analysts CISO SE, SOC Analyst

The primary risk was overwhelming users with interconnected data before they were ready to interpret or trust it.

8 Weeks end-to-end
3 User types
3 Project goals
3 Design pillars

I was responsible for shaping how these capabilities came together into a coherent experience — particularly how existing users transition into a relationship-based exposure model without losing trust in the platform they already relied on.

The challenge was not introducing new capabilities, but reshaping how users understood exposure.

Users were used to evaluating cloud posture and assets in isolation. The introduction of a knowledge graph shifted representation from lists to relationships, requiring a fundamental mental model change.

Critical risks

Overwhelming users with interconnected data, and losing trust if exposure relationship calculations were not transparent or explainable.

01

Existing customers needed familiarity and continuity to avoid disruption.

02

Sales required visible, differentiated capabilities to position the platform as exposure management.

03

Engineering constraints around evolving data pipelines limited how quickly and completely relationships could be surfaced.

Design decisions were made by continuously negotiating these tensions rather than optimizing for any single stakeholder. Each decision was made to manage adoption risk first, even when it limited feature visibility or technical completeness.

Project Goals

  1. Preserve familiarity while introducing a new exposure model

    Enable existing users to continue core workflows while gradually introducing relationship-based views of exposure.

  2. Make complex relationships understandable and trustworthy

    Represent assets, controls, and attack surface connections in a way users can interpret and validate.

  3. Support sales-critical narratives without compromising usability

    Surface exposure management capabilities clearly, without overwhelming day-to-day users.

Design Priorities

  1. Progressive transition of mental models

    Introduce connected views incrementally, anchoring new concepts to familiar patterns and language.

  2. Explainability over abstraction

    Ensure users can trace how exposure is derived, reinforcing trust in the system.

  3. Scalable structure within technical constraints

    Design layouts and interactions that adapt as data maturity improves, without frequent rework.

01 Connected Exposure Context

Knowledge Graph as the shared foundation — CCM and ASM built on top, creating a unified view of exposure rather than separate tools. Every finding links back to affected assets, controls, and business units.

02 Continuous Exposure Visibility

Real-time exposure scores with trend data — not a periodic snapshot but a living picture of risk that updates with the environment. Analysts can see exposure change as remediation happens.

03 Action-Oriented Views

Every insight surfaces a clear next step — from CISO-level dashboards down to analyst investigation flows. No dead-end summaries; everything routes to a remediation path.

prevalent.ai / exposure-overview
Exposure Score
72 RISK SCORE
High Risk
CCM Coverage
84%
↑ 3.2% this week
Attack Surface
1,247
↑ 42 new assets
Active Findings
318
↑ 12 since yesterday
Top Findings
AssetSeverityStatus
api.gateway Critical Open
auth-service High Open
db-cluster-01 Medium Resolved
cdn-edge-02 Low Open
Knowledge Graph · Finance BU
HOST CVE BU CTRL FIND RISK
  1. 01
    Preserve Familiar Entry Points

    User disorientation and resistance to change. New exposure capabilities were anchored to existing navigation and workflows, allowing users to adopt connected views without abandoning familiar paths.

  2. 02
    Progressive Exposure of Relationships

    Cognitive overload and loss of trust. Rather than enabling unrestricted graph exploration, relationships were revealed selectively where they directly supported user intent and decision-making.

  3. 03
    Sequenced CCM and ASM Views

    Information overload from simultaneous context shifts. Posture, assets, and exposure were introduced in a deliberate sequence, helping users build understanding incrementally instead of confronting everything at once.

Deliberately Avoided

  1. 01 Full graph exploration upfront
  2. 02 Advanced configuration in early phases
  3. 03 Exposing all relationships by default
Clarity Over Complexity

Dense security data is organized using clear visual hierarchy and structured layouts to support fast scanning and comprehension.

Reduced Cognitive Load

Progressive disclosure, spacing, and grouping are used to manage complexity and prevent users from being overwhelmed.

Speed & Reliability

Interaction patterns and visual language remain consistent across views to support predictable, efficient workflows.

Security Analysts + CISO Users
Design Lead Role
8 Weeks Timeline
Next Project Studio — Agentic Data Fabric