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Case Study - Gen AI

AI-Powered Customer Quote Generation Automation

Case Study - Gen AI

AI-Powered Customer Quote Generation Automation

AI-Powered Sales Quote Automation Services

AI & GenAI Solutions

A major U.S.-based Energy Company was facing operational challenges due to inefficient and outdated wind power forecasting methods. Their internal process relied heavily on manual analysis of production charts, making it:A major U.S.-based Energy Company was facing operational challenges due to inefficient and outdated wind power forecasting methods. Their internal process relied heavily on manual analysis of production charts, making it

The Challenge

A Fortune 200 manufacturing company was struggling with a slow and highly manual quote generation process. Every customer RFQ (Request for Quote) required Inside Sales Engineers to manually review documents, identify products, calculate pricing, validate terms, and prepare quotations.
As RFQ volumes increased, the process became difficult to scale. Sales teams spent valuable time on repetitive administrative tasks instead of engaging with customers and driving revenue.

The organization faced several challenges:

Manual extraction of information from RFQ documents

Time-consuming quote preparation and validation

Inconsistent quote formats across teams

Delayed customer responses during peak demand periods

Increased risk of pricing and data-entry errors

These inefficiencies directly impacted sales productivity, customer experience, and revenue
growth.

What JBS Built

Jade Business Services designed and implemented an AI-powered Sales Quote Automation Platform that automates the complete RFQ-to-Quote process using Agentic AI.
The solution enables sales teams to upload RFQ documents and automatically generate accurate, customer-ready quotations within minutes.
Instead of relying on manual review, multiple AI agents collaborate to extract information, calculate pricing, validate business rules, and generate final quotes.

The Challenge

Manual RFQ Processing Delaying Sales Cycles

A Fortune 200 manufacturer struggled with a manual quote generation process, slowing down RFQ responses and harming customer experience. Inside Sales Engineers were overwhelmed by repetitive tasks, leaving little time for strategic engagement. Core issues included:

Inefficient RFQ data extraction

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Inconsistent quotation formats

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Inability to scale during peak demand

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Missed sales opportunities due to delayed responses

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Business Impact

Lost Revenue and Decreased Sales Productivity

These inefficiencies resulted in:

Delayed quote turnaround times and lower conversion rates and lower conversion rates

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Inconsistent customer experiences affecting brand trust

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Sales team burnout from manual quoting workloads

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Reduced operational scalability and slower sales growth

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How the Solution Works

RFQ Intake & Document Processing

Users upload RFQ documents through a simple web interface.
The platform automatically processes structured and unstructured documents, including customer requirements, product specifications, delivery terms, and pricing information.

AI-Powered Information Extraction

Specialized LLM-based agents analyze RFQ documents and identify:

Product SKUs

Customer requirements

Pricing parameters

Delivery conditions

Commercial terms

These inefficiencies directly impacted sales productivity, customer experience, and revenue
growth.

Intelligent Quote Generation

The platform orchestrates multiple AI agents, each responsible for a specific task:

Pricing Calculator Agent

Calculates product pricing

Applies discount rules

Performs pricing validations

Document Generation Agent

Creates standardized customer-ready quotations

Applies discount rules

Generates final quote documents automatically

Quote-to-Cash Integration

The solution integrates seamlessly with existing business systems, including:

ERP platforms

CRM applications

Quotation management systems

This enables automated approval workflows, pricing governance, and quote tracking across the organization.

Scalable RFQ Processing

The platform supports parallel processing of multiple RFQs simultaneously.
Advanced Contract Negotiation Pricing (CNP) logic and real-time discount validation ensure that every quote aligns with business policies while maintaining speed and accuracy.

The Solution

How the Solution Works

RFQ Intake & Document Processing

Users upload RFQ documents through a simple web interface.
The platform automatically processes structured and unstructured documents, including customer requirements, product specifications, delivery terms, and pricing information.

AI-Powered Information Extraction

Specialized LLM-based agents analyze RFQ documents and identify:

  • Product SKUs
  • Customer requirements
  • Pricing parameters
  • Delivery conditions
  • Commercial terms

Intelligent Quote Generation

Specialized AI agents collaborate to create accurate, customer-ready quotations automatically.

  • Dynamic price calculations
  • Automated discount application
  • Pricing rule validation
  • Consistent quote formatting
  • Customer-ready documents

Quote-to-Cash Integration

Seamless integration with existing business systems enables automated approval workflows, strengthens pricing governance, and provides comprehensive quote tracking across the organization, including:

  • ERP platforms
  • CRM applications
  • Quotation management systems

Scalable RFQ Processing

The platform supports parallel processing of multiple RFQs simultaneously.

Advanced Contract Negotiation Pricing (CNP) logic and real-time discount validation ensure that every quote aligns with business policies while maintaining speed and accuracy.

Business Outcomes

01

70% Faster Quote Turnaround

Automated RFQ processing dramatically reduced the time required to generate customer quotations, enabling faster response times and improved sales velocity.

03

Greater Operational Scalability

The platform can process multiple RFQs simultaneously, allowing the organization to handle growing customer demand without increasing manual effort.

02

20% Increase in Sales Team Productivity

By eliminating repetitive administrative work, sales engineers were able to focus more on customer engagement, opportunity development, and revenue-generating activities.

04

Improved Quote Accuracy

Automated pricing calculations and business-rule validation reduced manual errors and improved consistency across all generated quotations.

05

Enhanced Customer Experience

Customers receive faster, more accurate, and professionally formatted quotations, improving responsiveness and strengthening customer relationships.

Technology Stack

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LangChain

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GPT

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Python

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Azure AKS

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React

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DevOps

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LangSmith

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AKS

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Technical Depth with Delivery Discipline

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Cloud-Agnostic Execution

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Embedded Governance

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Deep Industry Expertise

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Faster Time-to-Value

CASE STUDIES

Real Transformation. Measurable Results.

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    Business Value Delivered

    By implementing an Agentic AI-powered Quote Automation Platform, Jade Business Services transformed a traditionally manual sales process into an intelligent, scalable, and highly efficient workflow.

    The solution enables sales teams to upload RFQ documents and automatically generate accurate, customer-ready quotations within minutes.

    The solution reduced quote turnaround time by 70%, improved sales productivity by 20%, enhanced pricing accuracy, and enabled the organization to respond to customer opportunities faster than ever before.