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Logistics verified Verified Outcome TRL 9

Intelligent Document Processing (IDP) for Logistics

domain Client: A global logistics and mail company handshake Provider: UiPath / ABBYY schedule Deploy: Q3 2019 (Scale)
89 Impact
Enterprise Ready
Evidence Score: 5/10
Strength: High

Executive Summary

ANALYST: COI RESEARCH

Handling a massive variety of shipping manifests, customs forms, and invoices in different languages, the logistics giant deployed an AI-powered IDP solution. The system combines OCR with Machine Learning to classify document types, extract unstructured data, and feed it into RPA bots for processing in legacy systems.

rate_review Analyst Verdict

"A strong use case for 'Intelligent Automation' in high-variance environments. Standard OCR fails with unstructured logistics documents. Adding the ML classification layer allowed the entity to automate complex, non-standard invoicing workflows that previously required human eyes."

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Full Audit Report Available Includes Risk Register, Technical Specs & Compliance Data.

warning The Challenge

The company receives documents in thousands of formats from 220 countries and territories. Manual data entry for customs invoicing and vendor payments was slow, error-prone, and unscalable during peak shipping seasons.

psychology The Solution

Deployed UiPath robots integrated with ABBYY FlexiCapture. The system learns new document templates over time. If confidence is low, a 'human-in-the-loop' validates the data, retraining the model. The validated data is then entered into SAP by bots.

settings_suggest Technical & Deployment Specs

Integrations
SAP, Mainframe
Deployment Model
On-Prem / Cloud Hybrid
Data Classification
Commercial / Logistics
Estimated TCO / ROI
Medium
POC Summary (2017-01-01 to 2018-01-01)

"Pilot in Supply Chain division."

shield Risk Register & Mitigation

Risk Factor Severity Mitigation Strategy
Model Drift Medium Continuous retraining on new vendor templates.
Bot Stability Medium Robust exception handling frameworks.

trending_up Impact Trajectory

Audited value realization curve

Processing of millions of pages annually Verified Outcome
Primary KPIReduction in manual data entry effort
Audit CycleImproved SLA adherence during peak season

policy Compliance & Gov

  • Standards: Customs Regulations
  • Maturity (TRL): 9
  • Evidence Score: 5/10
  • Data Class: Commercial / Logistics

folder_shared Verified Assets

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Verified Case Study
PDF • Version 1
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Technical Audit
PDF • Audited
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Security Architecture

The "Blind Verification" Protocol

How we verified these outcomes for A global logistics and mail company without exposing sensitive IP or identities.

Private
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1. Raw Evidence

Audit ID: #PRIV-913
Evidence: Direct SQL Logs
Public
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2. Verified Asset

Outcome: Verified
Ref ID: #COI-913

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