Streamlining Order Management
A leading packaging manufacturer managing an extensive catalog of over 10,000 products faced operational inefficiencies in its order management process. The company served a diverse customer base, including small restaurants and large supermarket chains, where orders were primarily received via email in varying formats. Due to the absence of a standardized order submission process, three full-time employees manually processed and entered orders into the ERP system, leading to frequent errors and delays.
Business Objective
The key objective was to optimize the order management workflow by reducing reliance on manual data entry, improving order accuracy, and accelerating processing times. Given the high volume and diverse nature of customer orders, an intelligent automation solution was required to extract, validate, and standardize order information before integrating it into the company’s ERP system.
How We Accomplished It
The Codino team developed an AI-driven order processing agent capable of interpreting natural language from email orders, identifying product names, and standardizing varying units of measurement. The solution employed machine learning models trained on historical order data to accurately map customer-specified product descriptions to the company’s inventory database. Additionally, an OCR-based module was integrated to extract order details from scanned documents and attachments. The system performed real-time validation and flagged discrepancies for human review before seamlessly forwarding verified orders to the ERP platform.
The Results
Operational Efficiency: The automation of order processing resulted in a significant reduction in manual workload, allowing employees to focus on higher-value strategic tasks.
Time Savings: The company saved over 350 work hours per month by eliminating the need for manual data entry.
Error Reduction: Automated validation minimized order inaccuracies, ensuring improved fulfillment accuracy and reducing customer complaints.
Faster Processing: Orders were processed in near real-time, enhancing customer response times and satisfaction.
Ready to boost your business?
Unlock the potential of AI—streamline logistics with optimized supply chains, detect fraud in healthcare insurance, or use advanced social listening to strengthen your portfolio companies.
A leading packaging manufacturer managing an extensive catalog of over 10,000 products faced operational inefficiencies in its order management process. The company served a diverse customer base, including small restaurants and large supermarket chains, where orders were primarily received via email in varying formats. Due to the absence of a standardized order submission process, three full-time employees manually processed and entered orders into the ERP system, leading to frequent errors and delays.
Business Objective
The key objective was to optimize the order management workflow by reducing reliance on manual data entry, improving order accuracy, and accelerating processing times. Given the high volume and diverse nature of customer orders, an intelligent automation solution was required to extract, validate, and standardize order information before integrating it into the company’s ERP system.
How We Accomplished It
The Codino team developed an AI-driven order processing agent capable of interpreting natural language from email orders, identifying product names, and standardizing varying units of measurement. The solution employed machine learning models trained on historical order data to accurately map customer-specified product descriptions to the company’s inventory database. Additionally, an OCR-based module was integrated to extract order details from scanned documents and attachments. The system performed real-time validation and flagged discrepancies for human review before seamlessly forwarding verified orders to the ERP platform.
The Results
Operational Efficiency: The automation of order processing resulted in a significant reduction in manual workload, allowing employees to focus on higher-value strategic tasks.
Time Savings: The company saved over 350 work hours per month by eliminating the need for manual data entry.
Error Reduction: Automated validation minimized order inaccuracies, ensuring improved fulfillment accuracy and reducing customer complaints.
Faster Processing: Orders were processed in near real-time, enhancing customer response times and satisfaction.
Ready to boost your business?
Unlock the potential of AI—streamline logistics with optimized supply chains, detect fraud in healthcare insurance, or use advanced social listening to strengthen your portfolio companies.
Streamlining Order Management
A leading packaging manufacturer managing an extensive catalog of over 10,000 products faced operational inefficiencies in its order management process. The company served a diverse customer base, including small restaurants and large supermarket chains, where orders were primarily received via email in varying formats. Due to the absence of a standardized order submission process, three full-time employees manually processed and entered orders into the ERP system, leading to frequent errors and delays.
Business Objective
The key objective was to optimize the order management workflow by reducing reliance on manual data entry, improving order accuracy, and accelerating processing times. Given the high volume and diverse nature of customer orders, an intelligent automation solution was required to extract, validate, and standardize order information before integrating it into the company’s ERP system.
How We Accomplished It
The Codino team developed an AI-driven order processing agent capable of interpreting natural language from email orders, identifying product names, and standardizing varying units of measurement. The solution employed machine learning models trained on historical order data to accurately map customer-specified product descriptions to the company’s inventory database. Additionally, an OCR-based module was integrated to extract order details from scanned documents and attachments. The system performed real-time validation and flagged discrepancies for human review before seamlessly forwarding verified orders to the ERP platform.
The Results
Operational Efficiency: The automation of order processing resulted in a significant reduction in manual workload, allowing employees to focus on higher-value strategic tasks.
Time Savings: The company saved over 350 work hours per month by eliminating the need for manual data entry.
Error Reduction: Automated validation minimized order inaccuracies, ensuring improved fulfillment accuracy and reducing customer complaints.
Faster Processing: Orders were processed in near real-time, enhancing customer response times and satisfaction.
Ready to boost your business?
Unlock the potential of AI—streamline logistics with optimized supply chains, detect fraud in healthcare insurance, or use advanced social listening to strengthen your portfolio companies.
Streamlining Order Management