Starting the Workflow
To start the workflow, we’ll add a contract template to a folder. The document is collected from a reliable and anonymized source, Sebrae, and stored on Google Drive. This act of saving the document serves as a trigger that kicks off the workflow!
AI Contract Processing
Once the contract is saved, the AI steps in. Its goal is to analyze the document, making comparisons and extracting relevant information. During the analysis, the AI is programmed to provide clear outputs, organized in a spreadsheet format, which include:
Risk Score: A 0 to 100 assessment that indicates the level of risk associated with signing the contract.
Attention Points: A list of 10 items highlighting clauses or important information that deserve more detailed analysis.
Conclusion: A summary that organizes the points in a way that makes them easier to read and understand.
Analyzing the Results
After completing the processing, the user can review the outputs generated by the AI. For example, one of the points of attention may include clauses that imply full reimbursement liability. The user can easily confirm if the AI correctly read the document and found the relevant information, such as the specific clause mentioned.
Pedro illustrates this analysis by looking for details about liability for reimbursement and identifying potential issues, such as labor lawsuits and penalties, with the artificial intelligence highlighting fines and contractual responsibilities.
Comparison of Contract Models
Beyond analyzing a specific contract, the flow also allows for the comparison between different contract models. From the same initial trigger, the AI can compare Sebrae's contract with a company's own model, highlighting the differences. This provides a holistic view and a comprehensive analysis of clauses, offering insights into topics like duration and penalties that may be more or less favorable!
Flexibility and Customization
A remarkable feature of Tess is its flexibility. The AI is not limited to a single response format; it can generate analyses in different formats, like Google Docs, ensuring that the user can work in a customizable way, adapting to the specific needs of each legal situation, just as your prompt can define how the comparison will be.
Conclusion
The use of AI in contract analysis not only optimizes the time and resources involved in the task but also generates more precise and relevant results. This innovative approach represents a significant evolution in how companies handle legal documentation, as it brings modern technologies into the business routine!