Case Study
Federal Funding Flow
Designing an AI-powered workflow that connected federal budget planning to real-world spending.
Overview
What is this project?
Federal Funding Flow is a Bloomberg Government product that helps users track how federal money moves from proposal, to appropriation, to agency spending.
The product brought together budget data, line-item analysis, contract spending, related news, and key people into one workflow so users could monitor government priorities, qualify opportunities, and act faster.
Internally, it was positioned as a first-of-its-kind market differentiator and supported broader commercial goals around adoption, pricing, and sales enablement.
My Role
What did I do and why?
Turned fragmented research into a workflow
I helped shape a more unified experience that brought appropriations tracking, budget analysis, and spending visibility into one place. The goal was to reduce a manual, document-heavy process into a product users could actually navigate and act on.
Designed for complex data, not simplified data
I designed around a hierarchical funding model so users could move from high-level monitoring to detailed account-level analysis without losing context.
Integrated AI where it improved the experience
I designed features for summarization, Q&A, natural language querying, and comparison across legislative datasets, focusing on clarity, trust, and user control over system-generated insights.
Built patterns that could scale
I systematized interaction and visual patterns across hierarchy, state, and spacing so the product could stay coherent as it expanded across phases.
Constraints
Trade-offs and how I handled them
Messy source data
The product depended on appropriations bills, committee reports, OMB data, USASpending, and FPDS, some of which required ML extraction and human review. I designed for clarity and validation in places where confidence could vary.
Breadth vs. usability
The vision included budget tracking, spend analysis, related news, people, bill summaries, filters, and exports. I used hierarchy and progressive disclosure to keep the product usable without flattening the domain.
Automation vs. trust
AI-assisted interactions needed to feel helpful but never opaque. I focused on entry points and patterns that preserved user control and made outputs easier to validate.
Phased rollout vs. long-term system
Because the product launched in phases, I emphasized reusable patterns and scalable structure rather than optimizing too narrowly for one release.
Outcome
What was the impact?
Federal Funding Flow was designed to compress a slow, fragmented federal budget research process into a single connected workflow. Instead of manually stitching together appropriations documents, spending records, related news, and key contacts across disconnected sources, users could move through the analysis in one place.
“Having all the data in one place stacked together is just perfect.”
The clearest impact was workflow efficiency. In some lobbying use cases, gathering and analyzing the necessary budget information could take 4 to 6 weeks per client. Federal Funding Flow addressed that by centralizing the core workflow and making budget, spend, and contextual data easier to access, compare, and act on.