Legal Contract Compliance Verifier Using Hybrid LLMs and Rule Based Systems

Bhoomika Sai N; Sonali Sharma; Sadu Atchuta Rao; Komali Challa

doi:10.69968/ijisem.2026v5i2627-632

Authors

Bhoomika Sai N Data Engineering, MVGR College of Engineering, Vizianagaram, India
Sonali Sharma Data Engineering, MVGR College of Engineering, Vizianagaram, India
Sadu Atchuta Rao Data Engineering, MVGR College of Engineering, Vizianagaram, India
Komali Challa Andhra University, Visakhapatnam, India

DOI:

https://doi.org/10.69968/ijisem.2026v5i2627-632

Keywords:

Contract Compliance Checker, LLM (Large Language Models), Hybrid LLMs (Groq API & Ollama), Rule Based Systems, Legal NLP, Explainable AI

Abstract

In the recent corporate businesses, legal contracts are the foundation of business, employment, and partnerships, yet their manual review is often slow, costly, error-prone, and dependent on legal expertise. However traditional methods include ML models with large labelled datasets often lacking contextual understanding of legal language, transparency and cannot easily adapt to different legal situations. To overcome these limitations, we proposed now, a Legal Contract Compliance Checker that combines hybrid Large Language Models (LLMs) with a rule-based legal validation framework. The proposed system uses online LLM inference through Groq API for high-performance analysis and offline inference using Ollama to ensure data privacy. Legal contracts uploaded by users are preprocessed, analyzed semantically using LLMs, and validated against a structured rule engine derived from government portals, academic publications, and educational legal resources. After analyzing, the system classifies contract clauses into Safe, Concerning, and High-Risk categories and generates explainable compliance reports which may be downloadable and used for later. This approach assists legal practitioners, organizations, and non-expert users by reducing manual effort, improving accuracy, transparency and enabling faster and more reliable compliance checking, making it suitable for real-world legal applications.

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