Retail Operations with AI OCR: A Case Study in Workflow Simplification

Client Profile

With locations in major cities and a steadily expanding clientele, our client is a reputable multi-brand retail network. Among the many back-office tasks involved in their retail operations are inventory management, invoice processing, vendor interactions, and compliance reporting. With hundreds of papers handled every day across several sites, manual data input and verification was becoming an unsustainable and expensive burden.

Challenges

The retail team had to devote additional workers to repetitive operations like entering invoice data, matching shipping papers to orders, and reconciling purchase records as the firm grew. These procedures were resource-intensive, slow, and prone to mistakes. This not only led to significant operational expenses, but it also diverted employees' attention from more important duties like client interaction and vendor optimization. Additionally, delays in data entry led to difficulties in inventory updates, finance, and procurement. This not only led to significant operational expenses, but it also diverted employees' attention from more important duties like client interaction and vendor optimization. Additionally, delays in data entry led to difficulties in inventory updates, finance, and procurement.

Solutions

To reduce the operational load and streamline retail workflows, we deployed Percepta, our AI-powered OCR engine designed specifically for intelligent document processing in high-volume environments. Percepta automates the extraction and validation of data from purchase orders, shipping forms, and invoices by integrating via API into the client's ERP and financial systems. Its machine learning skills reduced the need for manual adjustments by enabling it to accurately adapt to a variety of document formats. The solution enabled uninterrupted real-time data flow throughout the client's retail operations thanks to its scalable cloud architecture.

Results

Percepta's deployment substantially reduced manual labor, reducing data input time by more than 80% for both back-office and core retail workflows. Fewer employees were needed for document processing, and the team members who were freed up were redirected to customer support, data analysis, and vendor management positions, which reduced operational expenses. Due to on-time payments and fewer disputes, the organization also improved financial reporting accuracy, expedited document turnaround, and increased vendor satisfaction. The customer successfully scaled retail procedures without correspondingly rising overhead after implementing Percepta