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Renewable Energy Company

Transforming Energy Industry Document Management with AI

A leading renewable energy provider implemented an innovative AI solution that automated their document management system, reducing processing time by over 70% and enabling efficient handling of tens of thousands of customer contracts while freeing up valuable staff resources for strategic activities.

Services

• Artificial Intelligence
• Strategy

Industry

• Energy & Utilities

OVERVIEW

Renewable Energy Company Reduces Document Processing Time by more than 70% with AI 

A leading renewable energy provider transformed its post-acquisition customer management approach via an innovative AI solution. By leveraging computer vision and generative AI, this function was largely automated, thereby achieving a more than 70% reduction in manual intervention. This breakthrough allowed the company to more efficiently process tens of thousands of customer contracts and service agreements, reduce risks and costs, enhance document accessibility, and free up valuable staff resources for more strategic activities.  

situation

Growth Creates Document Management Challenge    

As a major player in the renewable energy industry, the company’s growth strategy included regular acquisitions of installation companies and customer portfolios. Each acquisition brought thousands of critical customer documents in different formats, from contracts, support agreements, amendments, service documentation, equipment-related documentation, and more, creating an overwhelming document management challenge.  

Key challenges:   

• Processing backlog of tens of thousands of customer documents.
• Renaming and organizing documents according to company standards, document type, and customer. 
• Avoiding dedicating seven full-time staff to manual document processing.
• Improving the ease and speed of finding specific documents when needed. 

Impact

Manual Processing Threatens Business Growth   

Without modernizing their document management approach, the organization faced mounting operational risks that threatened their ability to scale effectively. The manual processing approach was creating significant business impact across the organization.   

Critical business impacts: 

• Difficulty accessing documents for legal and marketing needs. 
• Growing backlog with each new acquisition. 
• Limited ability to extract meaningful information from documents. 
• Long and costly manual process for processing documents.  

Resolution

Two-Phased AI Approach Delivers Results  

Allata partnered with the client to implement a two-phase AI solution development approach. The first phase was a three-week AI starter kit to prove viability, followed by a production implementation phase. The solution focused on classifying, renaming, and sorting documents along with matching them to customer records in their operational systems. 

Automation Enables Strategic Scaling   

The new system enables automated processing of acquisition-related documents, with capabilities for both automated matching and manual review when needed. The solution includes customer matching logic that adapts to variations in document formats and information. 

Solution highlights: 

• Automated document classification system.
• Customer matching with existing operational systems.  
• Ability to process tens of thousands of documents.  
• Integration with existing document management system.   

 

Technology

Modern AI Tech Stack Powers Solution 

Core technologies:

• Azure Functions
• C#
• OpenAI
• GPT-4o
• Semantic Kernel SDK
• Azure SQL Database
• React, Box API
• Service Bus Queues

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