Contract Negotiation Engine for Preference-Based Document Generation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional document creation and negotiation systems fail to automatically generate documents that balance the preferences of multiple parties, leading to time-consuming and costly negotiations, often requiring multiple rounds of revisions and professional intervention.
Innovation Solution
A system that utilizes a negotiation engine to obtain preference information from parties, generate ranking values for candidate contracts, and optimize an optimization function to determine a contract that satisfies the preferences of all parties, thereby automating the negotiation process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional redlining methods are used for document negotiation, then parties can review and modify contract terms, but the process becomes time-consuming and expensive requiring multiple rounds of exchanges
Solution Approach 1:
The system enables contracts to negotiate themselves automatically by comparing party preferences against contract terms and generating revised versions without human intervention. The automated negotiation engine processes multiple rounds of negotiations independently, eliminating the need for manual redlining exchanges between parties while maintaining agreement quality.
Solution Approach 2:
An automated negotiation engine acts as an intermediary between parties, receiving preference information from each party and generating optimized contract versions that balance competing interests. This intermediary system processes negotiations systematically, avoiding the inefficiencies of direct party-to-party redlining while preserving the ability to reach mutually acceptable agreements.
2Productivity
If default document templates are used, then document creation is simple and quick, but the documents may not cover particular situations or optimally reflect the interests of all parties
Solution Approach 1:
The system transforms static default templates into dynamic, adaptable documents through automated negotiation. The negotiation engine takes a default template and dynamically adjusts its terms based on real-time preference inputs from multiple parties, generating customized versions that maintain both creation efficiency and situational adaptability.
Solution Approach 2:
The system performs preliminary customization by pre-processing default templates with anticipated party preferences and generating optimized contract versions before final party review. This preliminary action reduces the need for extensive manual customization while ensuring the document reflects party interests from the outset.
3Adaptability or versatility
If manual redlining and multiple document exchanges are performed, then contract terms can be negotiated and adjusted, but the process becomes expensive requiring professional intervention
Solution Approach 1:
The system replaces the mechanical process of manual redlining and professional intervention with an automated computational negotiation engine. This engine systematically processes preference inputs, evaluates contract terms, and generates revised versions algorithmically, eliminating the need for expensive manual review cycles while preserving contract term flexibility.
Solution Approach 2:
The automated negotiation engine enables parties to negotiate contract terms independently without requiring professional mediators or lawyers. The system self-manages the entire negotiation process by comparing preferences, identifying conflicts, and generating balanced contract versions, reducing negotiation costs while maintaining adaptability.
Data Source
AI summary
Approaches provide for generating a document (e.g., a contract) that satisfies constraints of at least one party in negotiation. Information can be obtained from parties seeking to negotiate document sections (e.g., clauses or provisions) of a document such as a contract. Ranking values for a plurality of candidate contracts can be determined based on information from the parties, including their preferences for different sections (e.g., provisions) of the contract. The values can be used to optimize an optimization function that measures the degree to which candidate contracts satisfy the information provided by the parties. For example, an optimization technique, machine learning-based technique, or other appropriate technique can be utilized to determine a document or document information that satisfies the constraints of the parties. Thereafter, a contract can be selected and presented to the parties. The parties can execute the contract, modify, store, or otherwise interact with and/or process the contract.