LOGOS: The Legal Clause Contradiction Detector

Inspired by the logical debugging of positronic brains in Asimov's 'I, Robot' and the critical data analysis needed for survival in 'Interstellar', LOGOS is a tool designed to find the 'ghost in the machine' of legal texts. The project's foundation comes from the 'Technology Specifications' scraper, applying data extraction techniques to the dense world of legalese.

Concept:
Lawyers and paralegals spend countless hours drafting and proofreading documents to ensure they are airtight. However, human error in complex, lengthy contracts can lead to costly logical flaws. LOGOS is not a legal advisor; it is a specialized logic engine. It serves as an automated 'devil's advocate', rigorously checking the internal consistency of a document's text without attempting to interpret the law itself. This niche focus avoids the immense complexity of AI legal advising and creates a simple, powerful tool for solo practitioners and small law firms.

How it Works:
1. Ingestion & Parsing: A user securely uploads a document (e.g., .docx, .pdf) to a web application. Using Natural Language Processing (NLP) techniques, the system parses the text, identifying key components like definitions, obligations (e.g., 'shall', 'must'), prohibitions ('shall not'), and the parties involved. It essentially 'scrapes' the logical structure from the prose.

2. Logical Analysis (The 'Asimov' Engine): The core of the project is a rule-based engine that builds a knowledge graph from the parsed text. It then runs a series of checks inspired by formal logic:
- Contradiction Detection: Flags clauses that are mutually exclusive. For example, 'Clause 5.1: The Tenant shall not keep pets on the Premises.' and 'Appendix A: A pet deposit of $500 is required for dogs.'
- Ambiguity Highlighting: Identifies terms that are used inconsistently or defined vaguely, which could be exploited later.
- Circular Reference Check: Detects circular definitions, such as 'The 'Effective Date' is the date listed in the 'Agreement Summary'' and 'The 'Agreement Summary' is valid from the 'Effective Date''.

3. Reporting (The 'Interstellar' Interface): The output is not a revised document, but a clear, interactive report. Much like the simple, data-driven interfaces of the TARS and CASE robots, the report highlights problematic clauses, explains the logical fallacy in plain English ('Contradiction Found: An action is both permitted and prohibited'), and allows the user to instantly navigate to the conflicting sections in their original document.

Business Model:
This project is low-cost, relying on open-source NLP libraries and standard cloud hosting. Its high earning potential comes from a tiered SaaS model:
- Free Tier: Analyze documents up to 3 pages to attract users.
- Pro Tier: A monthly subscription for solo practitioners and freelancers with a generous document processing limit.
- Business Tier: A multi-seat license for small law firms, offering collaboration features and higher usage caps.