AI Profit Assistant

AI Profit Assistant

AI Profit Assistant

From static reporting to conversational profit analysis at transaction level

From static reporting to conversational
profit analysis at transaction level

From static reporting to conversational profit analysis
at transaction level

I designed an AI assistant embedded within an Enterprise Profit Management platform, enabling finance teams to move from manual analysis to instant, explainable answers grounded in a GL-reconciled profit model.

I designed an AI assistant embedded within an Enterprise Profit Management platform, enabling finance teams to move from manual analysis to instant, explainable answers grounded in a GL-reconciled profit model.

I designed an AI assistant embedded within an Enterprise Profit Management platform, enabling finance teams to move from manual analysis to instant, explainable answers grounded in a GL-reconciled profit model.

Lead Product Designer

Lead Product Designer

- Lead Product Designer

AI / Data / Collaboration

AI / Data / Collaboration

- AI / Data / Collaboration

Enterprise Profit Management

Enterprise Profit Management

- Enterprise Profit Management

The Problem with Profit Visibility

The Problem with Profit Visibility

Finance Teams Don’t Lack Data
- They Lack Clarity

Finance Teams Don’t Lack Data - They Lack Clarity

Answering simple questions like:

Answering simple questions like:

Which customers are truly profitable?

Which customers are
truly profitable?

Which customers are truly profitable?

Which products are eroding margins?

Which products are
eroding margins?

Which products are eroding margins?

This requires spending a large amount of time rebuilding models, reconciling assumptions & validating outputs across systems. This creates:

This requires spending a large amount of time rebuilding models, reconciling assumptions & validating outputs across systems. This creates:

Slow decision cycles

Slow decision cycles

Inconsistent answers

Inconsistent answers

Limited trust in the data

Limited trust in the data

Turning Profit Analysis into a Conversation

Turning Profit Analysis
into a Conversation

The Opportunity was to Remove the Friction Between Question and Answer

The Opportunity was to
Remove the Friction Between Question and Answer

The Opportunity
was to Remove the Friction Between Question and Answer

Instead of navigating dashboards, users could simply ask: “Who are my top customers by profit in 2024?” and receive:

Instead of navigating dashboards, users could simply ask:
“Who are my top customers by profit in 2024?” and receive:

Instead of navigating dashboards, users could simply ask:“Who are my top customers by profit in 2024?” and receive:

A direct answer

A direct answer

A direct answer

Transparent Breakdowns

Transparent Breakdowns

Transparent Breakdowns

Further Exploration

Further Exploration

Further Exploration

AI Assistant Built on a Profit Model

The assistant is not a generic chatbot.

The assistant is not a generic chatbot.

It is grounded in a transaction-level profit model that:

It is grounded in a transaction-level profit model that:

Reconciles to the General Ledger

Reconciles to the General Ledger

Updates every reporting period

Updates every reporting period

Reflects real operational costs

Reflects real operational costs

This ensures every answer is:

This ensures every answer is:

Accurate

Accurate

Traceable

Traceable

Finance Grade

Finance Grade

Ask Anything

Users can ask natural language questions about profitability across any dimension:

Users can ask natural language questions about profitability
across any dimension:

Users can ask natural language questions about profitabilityacross any dimension:

Customer

Customer

Product

Product

Facility

Facility

Supplier

Supplier

Every Answer is Backed by Visible Logic

Users can:

Users can:

See how results were calculated

See how results were calculated

Validate outputs with confidence

Validate outputs with confidence

Understand drivers of profit

Understand drivers of profit

Analysis Doesn’t Stop at the First Answer

Users can ask follow-ups to:

Users can ask follow-ups to:r a collaborative environment where teams can manage all their ai tools on a unified platform.

Compare Segments

Compare Segments

Identify Key Drivers

Identify Key Drivers

Drill Deeper

Drill Deeper

The Assistant Adapts to User Context

Users can ask follow-ups to:

Users can ask follow-ups to:

Embedded mode for quick insights

Embedded mode for quick insights

Embedded mode for quick insights

Full-screen mode for deep analysis

Full-screen mode for deep analysis

Full-screen mode for deep analysis

From Answering Questions to
Enabling Faster, Smarter Decisions

From Answering Questions to Enabling Faster, Smarter Decisions

From Answering Questions to
Enabling Faster, Smarter Decisions

Shared Workspaces for Analysis

Users can save and organize analysis into shared workspaces called Islands.

Users can save and organize analysis into shared workspaces called Islands. collaborative environment where teams can manage all their ai tools on a unified platform.

These allow teams to:

These allow teams to:

Build a shared understanding of profit

Build a shared understanding of profit

Store key findings

Store key findings

Collaborate on insights

Collaborate on insights

Designed for Enterprise Use

The assistant includes controls for:

The assistant includes controls for:

Data scope and permissions

Data scope and permissions

Model configuration

Model configuration

File uploads and context

File uploads
& context

File uploads and context

Ensuring flexibility without compromising governance.

Ensuring flexibility without compromising governance.

Assets That Give the Assistant Context

Assets That Give
the Assistant Context

Assets That Givethe Assistant Context

The assistant was designed to work with supporting files and business context, not
just platform data.

The assistant was designed to work with supporting files and business context, not just platform data.

The assistant was designed to work with supporting files and business context, not just platform data.

Users can upload and manage assets such as reports, spreadsheets, documents, and
reference material, giving the assistant additional context for analysis and follow-up questions.

Users can upload and manage assets such as reports, spreadsheets, documents, and reference material, giving the assistant additional context for analysis and follow-up questions.

Users can upload and manage assets such as reports, spreadsheets, documents, and reference material, giving the assistant additional context for analysis and follow-up questions.

This helps finance teams connect structured profitability data with the supporting knowledge
needed to interpret it.

This helps finance teams connect structured profitability data with the supporting knowledge needed to interpret it.

This helps finance teams connect structured profitability data with the supporting knowledge needed to interpret it.

From Days to Seconds

The assistant transforms how teams work:

The assistant transforms how teams work:

Reduces analysis time from days to seconds

Reduces analysis time from days to seconds

Eliminates manual model rebuilding

Eliminates manual model rebuilding

Increases trust in profitability insights

Increases trust in profitability insights

Most importantly, it enables faster, better decisions at every level of the business.

Most importantly, it enables faster, better decisions at every level of the business.

What This Enables

What This Enables

This project represents a shift from static reporting to dynamic, conversational analysis.

This project represents a shift from static reporting to dynamic, conversational analysis.

It lays the foundation for a future where AI moves beyond answering questions
- to actively guiding business decisions.

It lays the foundation for a future where AI moves beyond answering questions- to actively guiding business decisions.

My Role & Contribution

As Design & UX Lead for this project, I was responsible for:

Foster a collaborative environment where teams can manage all their ai tools on a unified platform.

Defining the product direction

Defining the product direction

Designing
the full experience

Designing the full experience

Creating interaction patterns for AI explainability

Creating interaction patterns for AI explainability

Ensuring alignment with finance workflows

Ensuring alignment with finance workflows

Defining the product direction

Creating interaction patterns for AI explainability

Designing
the full experience

Ensuring alignment with finance workflows