Automating Budgeting Workflows with AI

Capstone Project

— SEP 2025 - PRESENT —

OVERVIEW

Context

Context

PFF, LLC is a consulting firm that develops tools to help nonprofits, local governments, and small agencies manage their budgeting and financial planning more effectively.

InCEP Platform

The consulting firm partners with the InCEP (Integrated Capital and Expenditure Planning) platform, which allows organizations to plan, forecast, and report budgets using data-driven insights.

Emergency Missions

Searching Mission Assignments

Creating New Mission Assignments

Creating Cost Estimates

Problem

Problem

The InCEP platform presents a clunky and time-consuming experience, creating an opportunity for AI-driven automation.

Our primary objective was to develop a new financial planning and forecasting tool, inspired by the InCEP platform, that enables non-technical users to navigate, search, and interpret financial data more intuitively with the aid of AI.

Our primary objective was to develop a new financial planning and forecasting tool, inspired by the InCEP platform, that enables non-technical users to navigate, search, and interpret financial data more intuitively with the aid of AI.

My Contribution

My Contribution

For this year-long project, I led end-to-end user research efforts, championing a user-centered design process through the creation of user personas, user stories, and "How Might We" statements, drawing on existing interview data. I contributed actively to the mapping of InCEP user flows and brainstorming sessions for AI use cases.

I co-led the development of a comprehensive design system from scratch, including components such as side navigation, buttons, cards, and form elements. Finally, I played an active role in usability testing, client presentations, and iterative design refinements.

For this year-long project, I led end-to-end user research efforts, championing a user-centered design process through the creation of user personas, user stories, and "How Might We" statements, drawing on existing interview data. I contributed actively to the mapping of InCEP user flows and brainstorming sessions for AI use cases.

I co-led the development of a comprehensive design system from scratch, including components such as side navigation, buttons, cards, and form elements. Finally, I played an active role in usability testing, client presentations, and iterative design refinements.

EMPATHIZE

Competitive Analysis

We started by conducting a competitive analysis to understand existing solutions in the space and how InCEP compares to them. For this, we analyzed popular budget forecasting platforms, including Euna Solutions, OneStream, OpenGov, and Cube Software.

Some insights include:

  1. Competitors like Cube and OneStream are moving toward purpose-built AI agents that handle specific financial tasks, not generic chatbots. There is an opportunity to eliminate the manual burden of the legacy InCEP platform rather than simply adding an AI layer on top of it.


  1. OneStream, despite being the most feature-rich platform, suffers from steep learning curves. If the tool requires extensive training, it will face adoption resistance.


  1. Across all competitors, the strongest dashboard patterns share top-level KPIs at a glance with drill-down detail below.


  2. No AI-powered budgeting tool exists specifically for emergency management organizations.

Understanding InCEP Workflow

We mapped core workflows across three key InCEP modules: Emergency Missions, Finance, and Admin, to identify pain points and opportunities for improvement.

We mapped core workflows across three key InCEP modules: Emergency Missions, Finance, and Admin, to identify pain points and opportunities for improvement.

I began with a hypothesis journey map from a self-guided system review, then led six remote, semi-structured 1:1 interviews (60–90 minutes) with call center agents who understood the licensing process and its pitfalls inside out.

I began with a hypothesis journey map from a self-guided system review, then led six remote, semi-structured 1:1 interviews (60–90 minutes) with call center agents who understood the licensing process and its pitfalls inside out.

Led call-centre agent interviews using a custom Excel guide outlining key steps across six core workflows

Past Interviews

Then, we led three remote, semi-structured 1:1 interviews (60–90 minutes) with end-users. This helped us directly empathize with the unique experiences of small company users.

Then, we led three remote, semi-structured 1:1 interviews (60–90 minutes) with end-users. This helped us directly empathize with the unique experiences of small company users.

Interviewing end users to assess RC perception and understand user journey

DEFINE

User Personas

Using Miro, I organized all research insights under six key workflow categories. From there, I extracted user pain points and identified over 25 issues that directly informed six journey maps.

Using Miro, I organized all research insights under six key workflow categories. From there, I extracted user pain points and identified over 25 issues that directly informed six journey maps.

Affinity mapping to extract user behaviors and pain points

User Stories

IDEATE

Design Goals

Reduce Visual Clutter

How might we create a clearer, more focused homepage that helps users find what they need?

Simplify Navigation

How might we help users locate licensing checklists and key resources faster?

Improve Search

How might we help users find specific information without feeling overwhelmed?

Clarify Language

How might we make NMLS terminology accessible to first-time small business users?

Keep Content Current

How might we ensure users always have access to accurate, up-to-date information?

AI Use Case Selection

Insights synthesized from user research drove feature prioritization and design recommendations.

Insights synthesized from user research drove feature prioritization and design recommendations.

How might we create a clearer, more focused homepage that helps users find what they need?

Task-Based Information Architecture

  1. Removed competing content sections like NMLS News, Agency News, and Popular Links.


  2. Persistent sidebar navigation.


  3. Reduced cognitive load and resources organized by user type and task.

How might we help users locate licensing checklists and key resources faster?

Elevated Checklist Visibility & Persistent Navigation

  1. Checklists moved from buried links to primary placement on homepage.


  2. Breadcrumb wayfinding allows users to see their location and navigate back easily.


  3. Multiple access points.

How might we help users find specific information without feeling overwhelmed?

Global Persistent Search

  1. Persistent, prominent search bar accessible from every page.


  2. Contextual search within sections allows users to search within their current area for more relevant results.

How might we make NMLS terminology accessible to first-time small business users?

Integrated Glossary Access

  1. NMLS Glossary surfaced on homepage as well as internal sections, previously buried deep in documentation.


  2. Glossary sits alongside related policy content, so users can reference terms while completing tasks.

How might we ensure users always have access to accurate, up-to-date information?

Dynamic Content Management

  1. Replaced static PDFs with XML-based content.


  2. Content editors can push changes instantly without regenerating and re-uploading entire documents.


  3. Broken links, duplicates, and outdated pages are gone.

Information Architecture

Information Architecture

I led the creation of the following Information Architecture:

I led the creation of the following Information Architecture:

PROTOTYPE

Design System

The Resource Center implements solutions addressing each pain point identified during research.

The Resource Center implements solutions addressing each pain point identified during research.

The redesigned NMLS Resource Center launched on September 20, 2025, directly addressing key pain points from our research: confusing navigation, information overload, and content that previously catered only to large companies.

The redesigned NMLS Resource Center launched on September 20, 2025, directly addressing key pain points from our research: confusing navigation, information overload, and content that previously catered only to large companies.

REFLECTION

Impact

Visibility

Synthesized and presented user research to VPs and Product Managers, bridging the gap between user insights and strategic product decisions.

Validation

Socialized the redesigned Resource Center with call center teams (the same users who informed our research) resulting in strong positive reception.

UX perception

Helped establish UX credibility within the business unit, showcasing how research-driven design leads to measurable product improvements.

Impact Stats

50%
reduction in navigation time across 10 common searches

~ 600 K
industry users impacted (state and federal Resource Center)

6
journey maps delivered, covering the most critical licensing workflows

Reflection

I completed my internship in August 2025 and was extended through the Fall semester. Working at the intersection of financial regulation and UX has taught me more than I can easily summarize, but here are the key takeaways:

  1. Empathy is key: Conducting user interviews revealed just how much is at stake in this industry. Every piece of instructional text, every button placement carries weight that can cost people their livelihoods. Designing with user empathy has never felt more essential.


  1. Data drives buy in, but stories create connection: Senior stakeholders need the numbers, user counts, error rates, conversion metrics. But user stories are what make those numbers resonate. Learning to weave both qualitative and quantitative methods into my journey maps has been one of the most rewarding parts of this work.


  1. Pivot often: Real-world projects are rarely linear. We started with a vague goal of improving self-service for small company users, paused, and shifted to understanding their pain points. That detour uncovered insights that shaped key decisions and informed tree testing for the new NMLS Resource Center information architecture.


  1. Small discoveries snowball: This research also helped us improve support for call center agents. A deep dive into ServiceNow call center data revealed untapped potential for UX improvements we hadn't anticipated.

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