AI Solar Contract Analysis for Automated Life Cycle Costing
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Solution Overview
Problem
Solar energy contracts are complex and difficult for property owners to understand due to their technical complexity and financial implications, and existing software tools require manual data input, which can lead to errors and comprehension challenges.
Innovation Solution
An AI-based method using natural language processing (NLP) and a generative pre-trained transformer (GPT) to automate the analysis of solar energy contracts, extracting key insights and data for life cycle cost analysis, minimizing human error and ensuring comprehensible results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual data input is used in existing software tools, then flexibility in data entry is maintained, but human error increases and comprehension becomes challenging
Solution Approach 1:
The system performs self-service by automatically extracting data from solar energy contracts using AI document analysis, eliminating the need for manual data entry by property owners. The AI model reads and interprets the contract documents itself, identifying key parameters and populating the analysis fields automatically.
Solution Approach 2:
The patent replaces the mechanical manual data input process with an automated AI-based document analysis system. Instead of physically typing or copying data, the system uses natural language processing and machine learning models to extract and interpret contract information automatically.
2Loss of information
If complex solar energy contracts are analyzed manually, then detailed understanding can be achieved, but time consumption increases and errors occur
Solution Approach 1:
The AI document analysis module continuously processes contract information without interruption, extracting data across all sections of the contract in a single automated workflow. The system maintains continuous analysis from document ingestion through to generating the life cycle cost report, eliminating pauses and manual transitions.
Solution Approach 2:
The patent introduces an AI-based intermediary layer between the complex contract documents and the life cycle cost analysis. This intermediary automatically interprets the contractual language, identifies relevant financial terms, and translates them into structured data that can be processed by the cost analysis engine.
3Loss of information
If detailed contract terms are presented to property owners, then complete information is provided, but comprehension becomes difficult for average property owners
Solution Approach 1:
The system extracts only the most relevant and material information from the complex solar energy contracts, separating essential financial and technical details from peripheral contractual language. The AI identifies and extracts key parameters such as system cost, production estimates, financial terms, and warranty information while filtering out unnecessary legal boilerplate.
Solution Approach 2:
The patent transforms complex contractual parameters into simplified, standardized output formats that are easier to comprehend. The AI converts detailed contract clauses into structured life cycle cost reports with clear visual presentations of financial metrics, making the information accessible to property owners without technical expertise.
Data Source
AI summary
An artificial intelligence-based document and life cycle cost analysis method for solar energy contracts. This method includes two main modules, the AI-based document analysis module and the life cycle costs analysis module. The AI-based document analysis module uses natural language processing (NLP) and a generative pre-trained transformer (GPT) to summarize the key insights and deficiencies of a solar energy proposal or contract and extract the necessary input data for a life cycle cost analysis. The life cycle cost analysis module accepts the input data from the AI-based document analysis module, acquires additional data from other sources like the internet and runs the life cycle cost analysis for the solar energy proposal or contract. The entire process is automated to minimize human error and maintain high industry standards from start to finish. This ensures that the results are both professional and comprehensible for the average property owner.