A global IT services and consulting company sought to transform its internal quotation processes by implementing intelligent automation. With a complex product catalog and frequent international transactions, the organization aimed to boost efficiency, improve pricing accuracy, and reduce turnaround times.

The Challenge

The company managed approximately 30 quotation requests per day and encountered several operational bottlenecks:

• Material Code Complexity: Internal points of contact (POCs) often struggled to accurately identify correct product and supporting model codes.

• Currency Conversion Errors: Prices required conversion from Japanese Yen to USD, but inconsistencies due to real-time rate fluctuations introduced pricing inaccuracies.

• Invoice Generation Gaps: Even after invoices were generated, delays in sending them to clients were common, disrupting client communication and cash flow.

These inefficiencies led to increased manual workload, delayed client responses, and operational friction across teams.

Solution Deployed

Beam AI deployed a specialized Quotation Generation Agent, designed to intelligently manage and automate the entire quotation lifecycle. The solution consisted of three main components:

1. Accurate Product Identification

The AI agent automatically analyzes input requests to determine the correct product and associated model numbers, removing dependency on manual cross-referencing and reducing errors.

2. Real-Time Currency Conversion

Leveraging live exchange rate data, the agent seamlessly converts quotation prices from Japanese Yen to USD, ensuring pricing remains accurate and up-to-date.

3. End-to-End Quotation & Invoice Automation

Once data is validated, the agent autonomously generates quotations and invoices, instantly sending them to clients and closing the loop without manual intervention.

Results & Business Impact

Deployment of the agent delivered immediate and measurable improvements:

• 10% increase in accuracy of product identification.

• 7% improvement in quotation precision and correctness.

• Noticeable reduction in delays related to invoice dispatch and client communication.

The automation not only improved data accuracy but also freed up internal teams from repetitive tasks, allowing them to focus on higher-value activities.

Future Outlook

The success of this implementation has prompted the organization to explore additional avenues of automation, including:

• Enhancing the existing agent with new features (e.g., multilingual support, customer-specific pricing models).

• Extending AI automation into other business functions like customer support, procurement, and reporting.

With intelligent agents handling the heavy lifting, the company is positioned to deliver faster, more reliable service, all while scaling with minimal incremental effort.