Inaccuracy rate due to manual data management
30%
A Customer Success Story
The Road to GenAI Automation for Agile Logistics Enterprises
The Challenge
A privately owned, multinational logistics enterprise with revenues of over $500 million, operations in over 21 countries, and a global network of customers faced significant challenges with manual data management. Data fragmentation and manual data entry from various documents hindered operational efficiency, compliance, and optimal tariff utilization. The transfer of semi-structured logistics data through APIs and EDIs perpetuated data inaccuracies, compromising data integrity even further.
Data Volume → Productivity Loss
Data trapped in emails, PDFs, Word documents, and spreadsheets
80%
Data processed manually, severely hindering efficiency
90%
Employee time spent on document processing
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 global network of +85 offices, 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), trained on over 1 million data samples from more than 35,000 real-world emails, possesses a deep, contextual understanding of complex, sector-specific terminology for key freight and supply chain operations. Stargo's machine-learning GenAI models harness real-time data and deep industry context — empowering the provider to predict trends, solve problems, and identify cost savings through automated data analysis.
The Implementation
Despite operating a complex, customized technology stack across 21 countries and serving customers in 120, Stargo integrated within four non-disruptive weeks. This compatibility with existing systems empowered the global logistics provider to immediately harness Stargo's advanced GenAI capabilities — without costly infrastructure overhauls.
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
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:
Single / Multi-Lane Proposals