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Case Study Global Logistics Provider

Turning Years of Operational Email into Queryable Decision Intelligence

The "Optimization Mesh" — converts years of historical operational email into structured decision intelligence, capturing institutional knowledge and enabling data-driven operational optimization.

50K+ Email threads processed

The Challenge

What They Were Dealing With

Critical operational knowledge — past decisions, route preferences, supplier constraints, exception handling patterns — was trapped inside years of email threads. When experienced staff left or were unavailable, institutional knowledge walked out the door, leaving teams to re-learn lessons from scratch.

What We Built

The System

1

Historical email ingestion pipeline — processes years of operational email threads at scale

2

Entity and decision extraction — AI identifies requests, constraints, actions, and outcomes from email conversations

3

Queryable decision model — structured knowledge base that operators can search and query in natural language

4

Path feasibility intelligence — leverages historical decisions to assess route and operational feasibility

5

Continuous learning — model improves as new operational emails are processed and outcomes are tracked

Results

Measurable Impact

50K+

Email threads processed and structured

Years of operational email converted into queryable decision intelligence

< 30s

Query response time

Natural language queries answered in under 30 seconds, versus hours of manual email search

0

Knowledge lost to staff turnover

Institutional knowledge preserved regardless of personnel changes

Tech Stack: PythonLangGraphAzureOpenAIVector DB

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