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Case Study - Gen AI

AI-Powered Customer Quote Generation Automation

Case Study - Gen AI

AI-Powered Energy Sales Quote Automation Platform for Utilities

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A major U.S.-based Energy Company was facing operational challenges due to inefficient and outdated wind power forecasting methods.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production charts, making it:A major U.S.-based Energy Company was facing operational challenges due to inefficient and outdated wind power forecasting methods.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A Fortune 100 energy company was struggling with an outdated quotation process that relied heavily on manual data entry, spreadsheets, and disconnected systems. Generating customer quotes often required teams to gather information from multiple sources, validate contract details manually, and perform complex pricing calculations before a quote could be sent to brokers or customers. As energy prices fluctuated rapidly, even minor pricing errors could have a significant impact on deal profitability.

The organization faced several critical challenges:

Quote turnaround times ranging from 2 to 5 days

High correction and rework rates caused by manual processing

Limited visibility across customer, pricing, and contract data

Delayed responses to brokers and customers

Exposure to wholesale energy price volatility

Hundreds of hours spent weekly on repetitive administrative work

These inefficiencies slowed sales cycles, increased operational costs, and created unnecessary financial risk across the quote-to-cash process.

What JBS Built

Jade Business Services designed and implemented an AI-powered Energy Sales Quote Automation Platform built on Google Cloud Platform (GCP). The solution automates the complete RFQ-to-Quote lifecycle, enabling energy providers to process quote requests, validate contract information, calculate pricing, and deliver customer-ready quotations within minutes rather than days. Using Agentic AI and Large Language Models (LLMs), the platform eliminates manual bottlenecks while improving pricing accuracy, compliance, and operational efficiency.

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

Automated RFQ Intake

Energy quote requests are uploaded into the platform through a centralized interface.

LLM-powered extraction services automatically identify and capture critical information from RFQ documents, eliminating manual data entry and reducing processing effort.

Intelligent Market & Region Recognition

The platform analyzes geographic and market-specific information to ensure every quote is generated using the appropriate business and regulatory rules, including:

  • Service territories
  • Regulatory zones
  • Market conditions
  • Regional pricing considerations

Automated Validation & Data Enrichment

AI-driven validation engines verify critical inputs before pricing calculations begin, automatically identifying errors and missing information to prevent costly downstream corrections, including:

  • Contract types & Load profiles
  • Meter identifiers
  • Customer information
  • Partner and broker details

Dynamic Pricing & Quote Generation

The platform integrates with pricing engines and business rules to generate accurate energy quotes in real time.

Specialized AI agents calculate pricing scenarios while considering market conditions, contract structures, and customer-specific requirements.

This allows the sales team to generate consistent, compliant, and highly accurate quotations within minutes.

Approval Workflow & Broker Delivery

A human-in-the-loop approval framework routes generated quotes to managers for final review and approval.

Once approved, quotations are automatically delivered to brokers or customers through integrated communication workflows.

This creates a seamless and auditable quote approval process.

Automated Validation & Data Enrichment

The solution integrates directly with key business systems to create a unified quote-to-cash process and eliminate data silos across operations, including:

  • CRM platforms
  • ERP systems
  • Energy pricing engines
  • Customer management applications

Business Outcomes

01

Quote Turnaround Reduced from Days to Minutes

The platform reduced quote generation time from 2–5 days to less than 5 minutes, enabling the sales team to respond to opportunities significantly faster.

03

Protected High-Value Deal Margins

By improving pricing accuracy and reducing exposure to market fluctuations, the organization protected between $100K and $200K in potential margin impact per deal.

02

90% Reduction in Corrections and Rework

Automated validation and standardized workflows dramatically reduced manual errors and repetitive rework.


04

Increased Sales Velocity

Faster response times enabled brokers and customers to receive quotes sooner, improving win rates and accelerating deal closures.

05

Improved Operational Efficiency

Sales teams eliminated hundreds of hours of manual administrative work, allowing them to focus on customer engagement and revenue-generating activities.

Technology Stack

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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

    Jade Business Services transformed a slow, spreadsheet-driven quoting process into an intelligent, automated energy sales platform capable of generating accurate, compliant quotes in under five minutes.

    The solution reduced rework by 90%, protected deal profitability, accelerated sales cycles, and enabled the client to scale its energy sales operations with confidence while maintaining pricing accuracy and regulatory compliance.