New See where your enterprise data creates delays, rework, and leakage.Get a free Data Savings Estimate
Stargo

A Customer Success Story

Unlocking Operational Excellence in Mid-Market Logistics

The Challenge

A leading global logistics provider operates an extensive freight forwarding network with air, ocean, and ground transportation services. The enterprise prides itself on its agility and ability to deliver tailored solutions that meet its customers' ever-evolving needs — from scheduling to budgetary requirements. However, it was experiencing firsthand the impact of data-volume fragmentation, unstructured data, and the burdens of manual data management.

Massive Data Volume → Productivity Loss

Inaccuracy rate resulting from this manual approach

30%

Data trapped in emails, PDFs, Word documents, and spreadsheets

90%

Data existing in unstructured or semi-structured formats

90%

Employee time spent on manual data management

50%

Data Fragmentation → Revenue Loss

Drowning in Data

The overwhelming volume of manual data tasks consumed valuable employee time and resources, hindering strategic focus.

Revenue Leakage

Inconsistent data and limited visibility obscured accurate demand modeling and pricing strategies.

Operational Challenges

The manual processes, prevalent across a network spanning 190 major markets, were a major source of inefficiency and operational costs.

The Solution

The Solution

Stargo's proprietary suite of AI technologies structures, corrects, and enriches all incoming unstructured and semi-structured data. The Stargo Large Language Model (SLLM) brings a deep, contextual understanding of sector-specific freight and supply chain terminology, while machine-learning GenAI models harness real-time data and industry context — empowering the provider to predict trends, solve problems, and identify cost savings through automated analysis.

The Implementation

Operating across 190 markets on a customized technology stack, the provider integrated Stargo within four non-disruptive weeks. The platform's compatibility with existing systems let the team immediately leverage advanced GenAI capabilities without costly infrastructure overhauls.

StarDox intelligence application

Built to fit

System-Agnostic

Stargo operates as a layer above existing systems like ERP, TMS, and WMS for seamless integration and minimal disruption — regardless of the tech stack.

System-AgnosticVersatile Connectivity

The Transformation

Data Enrichment Across the Supply Chain

StarDox standardized and enriched data from all sources — emails, PDFs, shipping documents, and carrier contracts — creating a single source of truth for critical information across sales, procurement, operations, and customs.

Data EnrichmentEnhanced ProcurementOptimized Pricing & ProposalsStreamlined Customs Compliance
ROI analytics dashboard

The Results

27%

Productivity Boost

Automation freed the employee hours that manual data tasks once consumed, returning focus to strategic work.

4%

Margin Improvement

Enhanced data accuracy and real-time analytics enabled better pricing strategies and cost management.

5.1%

Conversion Rate Boost

Improved data insights led to more effective commercial strategies and customer service enhancements.

User Adoption

Operations

Data extraction, route optimization, and predictive analysis streamline fulfillment.

Procurement

AI-powered insights and improved data quality support more effective carrier negotiations.

Sales

Real-time data visibility and dynamic pricing models boost conversion rates.

Proof of Value: 6 Months

Partnering with Stargo, the enterprise transformed its data management — achieving more efficient operations, better decision-making, and enhanced customer experiences. Stargo's seamless integration empowered the business to embrace advanced technology without disrupting daily operations.

Next Steps

With the success of the initial implementation, the client is expanding its use of Stargo to include:

Get started

Start turning messy operational data into trusted transactions.

Connect sample data, see where manual work creates cost and leakage, and find out which workflow to automate first - in a limited, read-only review.