Strategic Intelligence Platform

MERIDIAN

Sovereign intelligence platform for multi-agency deployments

Designed the complete interface system for a SOVEREIGN intelligence platform serving civil intelligence agencies, military J2 commands, law enforcement directorates, and cyber investigation units — all from a single deployment. The core challenge was making one product feel native to four operational cultures.

Role
Lead UI/UX Designer
Platform
Web-based, multi-deployment
Scope
14+ screens, design system
Tool
Figma
Status
Active development

On this page: OverviewOpeningBriefDesign ThinkingUsersJourneysProblemsIAScreensDesign SystemOutcomes

Users
DG, Analysts, IOs, Admins
Platform
Classification-aware web app
Primary design problem
One platform for four institutional cultures
Outcome
Unified IA, persona-driven views, explainable AI

One platform, multiple institutional realities

Most enterprise platforms are built for one type of user, one workflow, and one organizational context. MERIDIAN needed to feel purpose-built for civil intelligence, military command, law enforcement, and cyber investigation without fragmenting into four separate products.

The client required a single unified intelligence platform replacing a fragmented ecosystem of case management systems, geospatial tools, analyst workstations, and reporting applications. The platform had to preserve procedural and legal differences between deployments while enabling shared technical infrastructure.

Research

User and organizational research established divergent workflows, legal constraints, and decision authorities across four personas—this framed persona-driven IA and feature priorities.

Synthesis

Affinity mapping and task analysis surfaced shared patterns and unique needs, guiding which modules would be persona-conditional versus universally available.

Ideation

Sketches and low-fi flows explored persona-first navigation, login persona selector concepts, and the Reality Canvas mental model for persistent investigation.

Prototyping

Interactive prototypes validated map-first interactions, Agent Theater layouts, and Why-Trace layered disclosure for AI explainability.

Testing

Iterative usability tests refined persona flows, clarified compliance visibility, and tuned density for long analytic sessions.

Delivery

Component handoffs and detailed interaction specs supported engineering implementation of persona-conditional rendering and complex canvas interactions.

Director General / J2 Chief

Requires synthesized national situational awareness, decision queue visibility, and concise authorization flow. Needs answers in under a few minutes without digging into operational detail.

Senior Intelligence Analyst

Core power user who builds cases, runs AI agents, constructs patterns, and authors briefs. Needs a persistent investigative workspace that supports long sessions.

Intelligence Officer

Handles assigned cases, validates matches, and escalates findings. Requires clear clearance boundaries and inline compliance visibility.

System Administrator

Manages users, approvals, and audit logs. Needs governance tools that prioritize operational hygiene and prevent compliance gaps.

DG
Morning threat assessment — Strategic Overview, authorize decisions, review Agent Theater summary. Total time: under 4 minutes.
Analyst
Building a case — Reality Canvas, Pattern Lab, Graph view, Why-Trace and Brief Composer — end-to-end without external tools.
IO
Processing assigned cases — Alerts, Case Library, verify agent matches, update entities, maintain RBAC compliance.

01

One platform, four institutional cultures

Navigation, terminology, and permissions must adapt per persona without fragmenting the product.

02

AI explainability as a legal requirement

Every AI claim must surface a traceable reasoning chain with source citations and compliance context.

03

Persistent investigative workspace

Analysts need multi-session continuity: live agents, persistent context, and non-destructive exploration tools.

04

Compliance is inline, not an afterthought

Legal and clearance indicators must be visible at the point of action, not appended as modal checks.

05

Pattern building for domain experts

Visual pattern tools must translate to plain language and run at scale without requiring data science skills.

Role determines reality

Persona-driven views make each role feel purpose-built while sharing underlying infrastructure.

The AI works for the analyst

AI outputs are transparent and require human gating for high-impact decisions.

Compliance is context

Inline legal signals and clearance badges reduce accidental authorization errors.

Investigation has depth

Persistent canvases, low visual-noise design, and session continuity support long investigations.

MERIDIAN IA — Persona-Conditional Navigation
Command
Strategic Overview
Geographic Intel
Regional Commands
Investigate
Reality Canvas
Case Library
Pattern Lab
Operate
Agent Theater
Brief Composer
Why-Trace
Manage
Case Analytics
Entities & Networks
Operational Metrics

These screens are the operational expression of the IA hierarchy above. They show how the four core zones — Command, Investigate, Operate, and Manage — translate into the product workflows users rely on.

Key screens that define MERIDIAN

Strategic Overview

Strategic Overview

Provides a synthesized national situational awareness view for senior leaders. The DG uses this screen to review the National Threat Index, authorization queue, and high‑priority operational briefs — enabling decisions in under four minutes without leaving the overview.

Primary Users
DG, Commanders
Key Design Decision
High-level overview with drill-down cards to preserve decision speed
Operational Outcome
Faster, confident operational decisions from a single authoritative view
Reality Canvas

Reality Canvas

The persistent investigative workspace where analysts build cases across Map, Graph, Timeline, Voice, and Crypto lenses. Context persists across sessions while live AI agents surface relevant matches.

Primary User
Senior / Tactical Analysts
Key Design Decision
Persistent canvas state with multi-lens explorer
Operational Outcome
Reduced investigation time; richer cross-source context
Pattern Lab

Pattern Lab

A visual, node-and-edge pattern builder that lets domain experts compose complex temporal and spatial detection rules without code. Matches translate to plain language and update live as the pattern is tuned.

Primary User
Threat Hunters
Key Design Decision
Visual rule composer with immediate feedback
Operational Outcome
Faster rule iteration and higher detection fidelity
Agent Theater

Agent Theater

Orchestrates specialized agents in parallel and exposes each agent's activity, outputs, and compliance posture. The three-column layout (Planner, Reasoning, Gated) makes autonomous vs. human‑gated activity visually explicit.

Primary User
Platform Operators
Key Design Decision
Explicit agent visibility and gating controls
Operational Outcome
Auditability and safer autonomous assistance

Component System & Tokens

Dark base, persona accent tokens, clearance typographic treatments, confidence bars, and rating badges form the visual language across modules.

Buttons
Tags & Badges
Blue Purple Green Amber Red Cyan
Alert Critical
Color Tokens
Blue
Brand
Cyan
Green
Amber
Red
System Tokens
Panel
#0E1223
Border
#1A2140
Text
#CBD5E1
Muted
#94A3B8
Decision

Login persona selector

We chose explicit persona selection at login to avoid ambiguous context inference — improves safety and reduces accidental cross-persona actions.

Login Screen

Artifacts

Persona matrices, IA specs, interaction flows, component library, prototype links, and test scripts were delivered alongside design tokens.

Handoff

Component handoffs included interaction specs for Pattern Lab, Why-Trace, and Reality Canvas to ensure consistent behavior across implementations.

Unified platform

Adapted interfaces reduced training friction and preserved organizational doctrines across deployments.

Faster investigations

Persistent canvases and live agents shortened time-to-insight across common case workflows.



Next steps: validate cross-persona handoffs and run usability tests for Pattern Lab and non-linear Brief Composer workflows.

Interested in complex operational design?