Veritas Ledger: A Blockchain-Based, Heuristic-driven NLP LegalTech Web Platform for Secure Document Verification
- DOI
- 10.2991/978-94-6239-713-2_52How to use a DOI?
- Keywords
- Blockchain; NLP; Spacy; Regex; Ethereum; LegalTech; SHA-256; Smart Contracts
- Abstract
In the transition from legal tech to online, we are faced with a problem: how to keep all our documents secure whilst ensuring that they are legally and constitutionally accurate. Blockchain is a secure means for creating a permanent record that cannot be tampered with. However, at the same time, it does not necessarily understand what the document entails. AI(NLP) can read and analyse a contract, looking for any technical discrepancies or problematic statements. To bridge this gap, proposed solution has been created, Veritas Ledger, a system that connects AI with the Ethereum Blockchain. It not only preserves your document but also reads it using smart analysis and flags potentially problematic clauses. Additionally, it verifies its structure before saving it on the blockchain. In our tests, the system was 87% accurate at spotting critical legal details and provided an unchangeable history of every contract version.
- Copyright
- © 2026 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Amruta Patil AU - Anushka Khot AU - Ananya Kulkarni AU - Aditi Menbudle PY - 2026 DA - 2026/06/25 TI - Veritas Ledger: A Blockchain-Based, Heuristic-driven NLP LegalTech Web Platform for Secure Document Verification BT - Proceedings of the International Conference on Advances in Computing Technology and Artificial Intelligence (COMPUTATIA 2026) PB - Atlantis Press SP - 704 EP - 716 SN - 2589-4919 UR - https://doi.org/10.2991/978-94-6239-713-2_52 DO - 10.2991/978-94-6239-713-2_52 ID - Patil2026 ER -