AI and Data Foundation Transforms $5BPetroleum Distributor, Driving $30M+ AnnualMargin Optimization

Cuesta partnered with a rapidly growingdistributor managing 30k monthly transactions onrazor-thin margins but lacking visibility into deal-level profitability. We built a modern AI and data foundation to quantify margins and proactively manage sales. Today, the company has automated decision-making across Finance, Sales, Logistics, and Supply, integrated data model across all areas , reduced negative transactions…
  • Data Modeling & Integration
  • Order Traceability
  • Margin Visibility Tools
  • AI Predictive Model
  • Automation

Challenges

  • The company managed around 30,000 monthly sales transactions with razorthin margins, but lacked visibility into deallevel profitability, making it impossible to proactively address margin leakage.
  • Leadership had limited insight into negative transactions, preventing timely action to reduce losses and optimize sales performance.
  • Legacy systems and fragmented processes created inefficiencies in financial reconciliation, tax reporting, and supply chain management, leading to inflated suspense
  • Without a robust data and AI foundation, the business could not automate decisionmaking or implement datadriven insight generation, leaving significant value untapped.

Solutions

  • Cuesta established a modern AI and data foundation to deliver full transactionlevel margin visibility, reducing negative transactions by 50% and enabling proactive sales management.
  • We deployed AIdriven predictive models and churn analysis to optimize pricing and retention, unlocking over $30M in annual margin optimization across Finance, Sales, Logistics, and Supply.
  • Through automation of AR/AP adjustments, we cleared inflated suspense accounts, surfaced $4.2M in client underpayments, and recognized an additional $2M in unreported revenue.
  • Excise tax reconciliation across districts and states recovered $12.8M in overpayments, while automation of invoicetocash processes reduced financial close cycles from over 20 days to weekly soft closes.