Pamoja streamlines its order management with AI-driven automation
Pamoja is a Swedish company specializing in modern platforms for media, education, and social engagement.
Client:
Pamoja
Introduction
As the volume of incoming orders increased, Pamoja needed a smarter way to handle data from multiple channels. Together with Euvic, they developed an AI-driven system that automatically interprets and structures order information. The result was faster processes, fewer errors, and a future-proof foundation for continued automation.
Challenge
Pamoja faced growing complexity in its order handling process. Orders arrived through multiple channels, emails, chat messages, and external systems. Often in unstructured formats.
This meant that employees spent significant time manually entering and verifying order data, a process that was both resource-intensive and prone to human error.
To overcome this, Pamoja set three clear objectives:
- Automate order extraction to reduce processing time and cost.
- Improve customer experience through faster and more seamless order handling.
- Build a scalable solution that could evolve as new AI models emerge.
Solution
To address these challenges, Euvic developed an AI-powered order extraction system built on Amazon Bedrock and Claude 3.5 Sonnet.
- The system uses advanced natural language processing (NLP) to interpret unstructured order inputs and automatically convert them into structured JSON format, ready for seamless integration with Pamoja’s internal systems.
- A validation workflow ensures quality by flagging incomplete or ambiguous orders for administrator review. Striking the right balance between automation and human oversight.
- Developed using .NET, React, and AWS, the solution provides both scalability and integration flexibility. Amazon Bedrock was chosen for its pay-as-you-go pricing model and the flexibility to easily switch between AI models as technology evolves.
- For the proof of concept, Claude 3.5 Sonnet was selected due to its superior accuracy, processing speed, and advanced natural language understanding capabilities.
Result
The implementation delivered immediate and measurable impact:
- Significantly reduced manual order entry time, allowing staff to focus on higher-value activities.
- Improved accuracy and consistency in order processing.
- Faster response times, enhancing the overall customer experience.
- A future-proof AI foundation ready to scale with new models and changing business needs.
Summary
By implementing an AI-driven order processing system, Pamoja successfully modernized a critical business workflow. Transforming a manual, time-consuming process into an intelligent, automated operation.
