Streamlined Delivery Operations through Machine Learning Image Classification

The Challenge

A last mile delivery leader faced challenges with manual package data tracking, leading to confusion over customer-provided data. An offshore team manually processed images, resulting in inconsistent classifications and high operating costs. Scalability was hindered compared to ML models.

The Solution

66degrees leveraged the capabilities of Google Cloud to ingest delivery photos, building a Machine Learning model for Virtual Proof of Delivery. We refined criteria, manually labeled images, and developed an ML model to automate the process, enhancing accuracy and efficiency for the client’s ELI delivery application.

The Result

Efficiency Boost: ML model outperformed offshore teams, reducing time, cost, and improving consistency.

Cost Savings: Reduced expenses compared to offshore teams, improving profitability.

Optimized Operations: Automated process allowed the client to operationalize previously manual tasks.

Enhanced Consistency: ML model ensured consistent results, improving overall operational efficiency.

About the Client

The client is the solution of choice for last-mile e-commerce deliveries that helps retailers and shippers build a competitive advantage through faster delivery times, lower costs, coast-to-coast coverage, and reliable on-time performance.

The companys footprint stretches across the United States to reach approximately 70% of the population in 35 states and Washington, D.C. and enhance retailers’ ability to meet growing demand in the consumer e-commerce delivery market.

Streamlined Delivery Operations through Machine Learning Image Classification

The Challenge

A last mile delivery leader faced challenges with manual package data tracking, leading to confusion over customer-provided data. An offshore team manually processed images, resulting in inconsistent classifications and high operating costs. Scalability was hindered compared to ML models.

The Solution

66degrees leveraged the capabilities of Google Cloud to ingest delivery photos, building a Machine Learning model for Virtual Proof of Delivery. We refined criteria, manually labeled images, and developed an ML model to automate the process, enhancing accuracy and efficiency for the client’s ELI delivery application.

The Result

Efficiency Boost: ML model outperformed offshore teams, reducing time, cost, and improving consistency.

Cost Savings: Reduced expenses compared to offshore teams, improving profitability.

Optimized Operations: Automated process allowed the client to operationalize previously manual tasks.

Enhanced Consistency: ML model ensured consistent results, improving overall operational efficiency.

About the Client

The client is the solution of choice for last-mile e-commerce deliveries that helps retailers and shippers build a competitive advantage through faster delivery times, lower costs, coast-to-coast coverage, and reliable on-time performance.

The companys footprint stretches across the United States to reach approximately 70% of the population in 35 states and Washington, D.C. and enhance retailers’ ability to meet growing demand in the consumer e-commerce delivery market.

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