About Us
Building legal AI that feels useful from day one
KanoonGPT was built to make Indian legal research faster, clearer, and more practical for students, professionals, and teams.
Focused Scope
Indian legal content, structured section by section for reliable retrieval and citation.
Practical Output
Explanations, summaries, and references that are actually usable in study and daily legal work.
Continuous Improvement
We ship updates regularly based on feedback from the legal community.
Who is behind KanoonGPT
The KanoonGPT team comprises AI engineers who worked at Anthropic and xAI, and law professionals from NLU Mumbai. That combination keeps us grounded: strong engineering standards on one side, and real legal context on the other.
We are not trying to build a flashy demo. We are building a dependable legal product that people can come back to every day.
Our mission
We are building KanoonGPT to make high-quality Indian legal intelligence accessible to everyone, not just large teams with large budgets.
Our goal is simple: deliver cost-effective, practically unlimited AI access powered by deeply structured Indian legal data so users can research, draft, and reason faster with confidence.
How we build
We focus on clean legal data pipelines, careful document processing, and product decisions that reduce confusion for users. Every feature has to answer one question: does this genuinely save time?
What we care about
Clarity over hype, speed without losing quality, and an interface that remains approachable even when legal material is complex.
How we differ from traditional legal tech
Platforms like SCC Online and Indian Kanoon are strong for search and reference. KanoonGPT is built for a different layer: reliable AI understanding on top of deeply structured legal documents.
Native OCR alone is not enough for Indian legal PDFs. A single section number can appear many times across headers, footers, cross-references, indexes, and case citations. If a user asks an AI tool, "Explain BNSS Section 20", many systems fail unless the prompt is expanded to "Explain Bharatiya Nyaya Suraksha Sanhita Section 20". Even then, they can still retrieve the wrong context because the document itself is ambiguously parsed.
KanoonGPT solves this through extensive PDF digitization with document understanding, not just text extraction. We map hierarchy, section boundaries, headings, citations, and context links before AI retrieval. That same pipeline is being applied across statutes and case law corpora, so answers are tied to the right legal unit, not just a matched number in raw text.
Want to explore KanoonGPT?
Browse the library, ask legal queries, and see the workflow yourself.