Sandbar.AI
Making financial-crime investigations easier to prioritize, investigate, and document
Sandbar.ai was an anti-money-laundering platform designed to help investigation teams identify suspicious activity, manage cases, and bring the evidence behind a financial-crime investigation into one structured workflow.
AML investigations require analysts to work across alerts, entities, accounts, transactions, risk signals, and supporting evidence. The challenge is not simply finding a potential issue—it is understanding what needs attention, how serious it is, who owns it, and what information supports the next decision.
I helped shape Sandbar’s product experience around that investigative workflow, creating a clearer system for triage, review, evidence collection, and case management.
Product Strategy
Content Strategy
Information Architecture
UX & UI Design
New Design System Creation
Responsive Desktop and Mobile Design
Scope
Role & Ownership
I led the product design work across strategy, research, journey mapping, wireframing, UX/UI design, and the creation of a new design system.
My role was to translate a complex, high-stakes compliance workflow into a product that helped investigation teams move from a risk signal to a structured, evidence-based case review.
The Real Problem
Financial-crime investigations can become difficult to manage when risk signals, accounts, entities, transactions, evidence, and case status are spread across disconnected views. Analysts need to know what requires immediate attention, understand the context behind an alert, and build a defensible record of the investigation.
The product needed to make that process clearer without hiding the details that teams need to evaluate risk and make informed decisions.
What Changed / Outcome
I designed a connected investigation experience that brought triage, case review, and evidence management into one product system.
The investigation dashboard prioritized new, assigned, unworked, rejected, high-risk, and aging cases. Teams could review risk scores, alerts, assigned ownership, case status, and investigation age from a single queue.
Detailed investigation views connected targets, alerts, evidence, history, risk typologies, rule outputs, and recommendations. Account and entity workflows allowed analysts to review related records and deliberately add selected items as evidence, creating a clearer path from raw data to a documented investigation.
The result was a cohesive product direction and scalable design system for Sandbar’s AML investigation platform.
