Published
Dec 23, 2024
Updated
Dec 23, 2024

Unlocking Contract Insights with AI

Contrato360 2.0: A Document and Database-Driven Question-Answer System using Large Language Models and Agents
By
Antony Seabra|Claudio Cavalcante|Joao Nepomuceno|Lucas Lago|Nicolaas Ruberg|Sergio Lifschitz

Summary

Imagine effortlessly navigating the complexities of legal contracts, instantly extracting key information without the need for tedious manual searches. This is the promise of Contrato360 2.0, a cutting-edge question-and-answer system that leverages the power of AI to revolutionize contract management. Traditional contract management systems often struggle to answer nuanced questions or provide comprehensive overviews. Contrato360 2.0 tackles this challenge by combining information from contract documents (PDFs) with data from contract management databases. It uses a sophisticated multi-agent approach, where different AI agents specialize in specific tasks. One agent uses Retrieval-Augmented Generation (RAG) to find relevant passages within the contract documents themselves. This agent cleverly breaks down the contracts into meaningful chunks by section, including crucial metadata like contract numbers to ensure accuracy. Another agent uses text-to-SQL technology to extract precise data points from the structured database. These agents work together, orchestrated by a 'router agent' that directs the flow of information based on the user's question. Furthermore, careful prompt engineering ensures the AI understands the nuances of legal language and delivers precise, relevant answers. In tests with contract specialists, Contrato360 2.0 demonstrated remarkable accuracy, quickly providing comprehensive summaries and answering complex questions. It even dynamically generates graphs for better visualization. While initial results are highly promising, the research team acknowledges the need for further refinement, particularly in understanding complex legal concepts. Future research aims to expand the system's capabilities to different contract types and refine its understanding of nuanced legal terminology. This groundbreaking research points toward a future where AI can unlock valuable insights from contracts, saving time and empowering businesses with a deeper understanding of their agreements.
🍰 Interesting in building your own agents?
PromptLayer provides the tools to manage and monitor prompts with your whole team. Get started for free.

Question & Answers

How does Contrato360 2.0's multi-agent approach work to process contract information?
Contrato360 2.0 uses a sophisticated multi-agent system where specialized AI agents handle different aspects of contract analysis. The system employs three main components: 1) A RAG agent that chunks and analyzes contract documents, maintaining context through metadata like contract numbers, 2) A text-to-SQL agent that queries structured databases for precise data points, and 3) A router agent that orchestrates information flow between agents based on query type. For example, when a user asks about payment terms, the router agent might direct the query to both the RAG agent (to find relevant contract clauses) and the SQL agent (to retrieve specific payment records), then synthesize a comprehensive response.
What are the main benefits of AI-powered contract management for businesses?
AI-powered contract management offers significant time and resource savings by automating document analysis and information extraction. It helps businesses quickly access key contract details, track obligations, and identify potential risks without manual review. For instance, a company can instantly find specific clauses across thousands of contracts or generate comprehensive summaries of complex agreements. This technology also reduces human error, ensures consistent interpretation, and enables better decision-making through quick access to contract insights. Whether you're managing vendor agreements or customer contracts, AI streamlines the entire process.
How is artificial intelligence changing the way we handle legal documents?
Artificial intelligence is revolutionizing legal document handling by making it faster, more accurate, and more accessible. AI systems can now automatically extract key information, identify important clauses, and answer specific questions about legal documents in seconds. This transformation means legal professionals can focus on high-value analysis instead of time-consuming document review. The technology also helps non-legal professionals better understand complex documents through plain-language summaries and automated insights. This democratization of legal document analysis is making contract management more efficient across all industries.

PromptLayer Features

  1. Workflow Management
  2. The paper's multi-agent orchestration approach directly aligns with PromptLayer's workflow management capabilities for coordinating complex prompt chains
Implementation Details
1. Create separate prompt templates for RAG and SQL agents 2. Define router logic for query routing 3. Set up orchestration pipeline with version tracking 4. Implement feedback loops for agent coordination
Key Benefits
• Centralized management of multiple specialized agents • Version control for complex prompt chains • Reproducible multi-step workflows
Potential Improvements
• Add automated agent performance monitoring • Implement dynamic prompt optimization • Enhance error handling between agents
Business Value
Efficiency Gains
50% reduction in workflow setup time through reusable templates
Cost Savings
30% reduction in API costs through optimized agent routing
Quality Improvement
90% accuracy in maintaining consistent agent interactions
  1. Testing & Evaluation
  2. The paper's focus on legal accuracy and specialist testing aligns with PromptLayer's comprehensive testing and evaluation capabilities
Implementation Details
1. Define test cases for legal contract scenarios 2. Set up A/B testing for prompt variations 3. Implement regression testing pipeline 4. Create scoring metrics for legal accuracy
Key Benefits
• Systematic evaluation of prompt effectiveness • Continuous quality assurance • Data-driven prompt optimization
Potential Improvements
• Add domain-specific evaluation metrics • Implement automated accuracy checks • Enhance test case generation
Business Value
Efficiency Gains
75% faster validation of prompt changes
Cost Savings
40% reduction in QA resource requirements
Quality Improvement
95% accuracy in legal response validation

The first platform built for prompt engineering