Skip to main content

Applied Work

LedgerShift Lab

Practical experiments in Finance, AI, FinOps, and technology economics.

The goal of the Lab is simple: learn by implementing. Each project starts with a real Finance or technology economics problem and works through the process of understanding the problem, designing an approach, implementing it, testing it, establishing appropriate controls, and measuring what happened.

Lab Projects

PROJECT 001Building
Case study coming soon

AI-Enabled Variance Analysis

An applied Finance AI workflow using structured financial data, SQL, and an LLM to automate the first draft of management variance analysis while retaining deterministic calculations and Finance review.

Areas

SQLFinancial AnalysisAI Workflow DesignModel EvaluationHuman-in-the-Loop Controls

Case Study Structure

  1. 01Business Problem
  2. 02Current State
  3. 03Requirements
  4. 04Solution / Workflow
  5. 05Implementation
  6. 06Data & Technical Approach
  7. 07Controls
  8. 08Evaluation Method
  9. 09Results
  10. 10What I Learned
  11. 11Supporting Artifacts

Supporting Artifacts

  • Workflow diagrams
  • SQL queries
  • Sample / synthetic datasets
  • Evaluation rubrics
  • Prompts
  • Requirements documents
  • Implementation briefs
  • Executive outputs
PROJECT 002Planned
Case study coming soon

Finance AI Workflow

Taking a recurring Finance process from current-state analysis through requirements, automation design, implementation, testing, controls, and ROI measurement.

Areas

Finance TransformationProcess DesignAI AutomationControlsROI Measurement

Case Study Structure

  1. 01Business Problem
  2. 02Current State
  3. 03Requirements
  4. 04Solution / Workflow
  5. 05Implementation
  6. 06Data & Technical Approach
  7. 07Controls
  8. 08Evaluation Method
  9. 09Results
  10. 10What I Learned
  11. 11Supporting Artifacts

Supporting Artifacts

  • Workflow diagrams
  • Process documentation
  • Requirements documents
  • Implementation briefs
  • ROI model
PROJECT 003Planned — October 2026
Case study coming soon

AI FinOps Implementation

An end-to-end simulated AI FinOps implementation for a growth-stage AI-native SaaS company, covering technology cost allocation, AI COGS, unit economics, budgeting, forecasting, governance, and management reporting.

Areas

FinOpsAI EconomicsCOGSUnit EconomicsForecastingGovernance

Case Study Structure

  1. 01Business Problem
  2. 02Current State
  3. 03Requirements
  4. 04Solution / Workflow
  5. 05Implementation
  6. 06Data & Technical Approach
  7. 07Controls
  8. 08Evaluation Method
  9. 09Results
  10. 10What I Learned
  11. 11Supporting Artifacts

Supporting Artifacts

  • Cost allocation models
  • Unit economics frameworks
  • Budget templates
  • Governance documentation
  • Management reporting outputs
  • Workflow diagrams

About the Lab

Each project is documented end-to-end.

When a project is complete, the full case study will be published here — including the business problem, approach, implementation, controls, evaluation, and what was learned. The Lab grows as the work progresses.

About Jillian