Vidhan uses advanced math for legal reasoning
to uncover the most effective strategies and solutions.
Designed by
Princeton math Ph.D. IIT alumniGuided by
experienced lawyers and judges
The lost argument
Every senior lawyer has experienced the pain of discovering a stronger argument after pleadings were filed, when there is little you can do with it
Unfortunately, that is also when partner attention is most fragmented across several matters. So only a few theories get explored when ten might exist.
Counsel must still decide if the material supports a theory, what counters will be raised and where it falls short, instead of exploring all possible alternatives to find the strongest argument. The result is a weaker case.
Pure Generative AI can be confidently wrong especially in familiar looking yet genuinely new scenarios. So counsel must check the output's accuracy - a hard task if the reasoning process is not exposed.
The lost hours
Our estimate is based on conversations with practising Indian lawyers, not a systematic time-use study.
Current legal AI seem useful. Summaries. Annotations. Drafts. But the law is still organized as tables and text—not as the relationships, constraints and implications you need to reason through a case. So the lawyer is still left to connect the dots before the next move becomes clear.
The inherited burden
“When you raise the dead, they bring their baggage.”
Databases inherited the library’s filing logic: year, court, citation, subject and keyword. They can find the pieces. They do not, by themselves, show how those pieces form an argument.
Other legal apps organise law for retrieval - a directory of locations and street names organized alphabetically. Vidhan organises law for reasoning - a city map of locations, streets, bridges, tunnels with speed limits, one-ways, roadblocks, busy intersections and so on. Which one would you need to drive to a new restaurant?
Powered by Vidhan Core our proprietary Reasoning Algorithms
Inside Reasoning Core
Vidhan Atlas is the mathematical map of law (or more accurately a higher dimensional analog of it). The reasoning core are the math algorithms that explore that map - finding the "best" path to go from evidence to the desired conclusion.
A Conceptual workflow analogy.
Translate legal principles, statutes and case law into higher dimensional mathematical representations - 'The Map'. Do the same for the facts and evidence of the specific matter to demarcate the region and locations on the map that are relevant - 'The City'.
Apply mathematical reasoning to survey different paths (argument chains), road blocks (counters), restricted zones (jurisdiction, limitations, distinguishing precedents) as well as potholes, animal crossings, potential traffic jams (risks).
Inspect - assumptions, supporting authorities and so on. Score the different paths based on requirements - fastest, shortest, safest, least crowded - weighing each against roadblocks and risks of each.
Language models have two restricted roles: translating human languages into mathematical representations and orchestrating the mathematical algorithms.
The strategy is built by the mathematical Reasoning Core.
Vidhan exposes the premises, reasoning steps, supporting authorities, and conclusions so they can be inspected against current legal sources.
Develop argument paths connecting facts, legal principles, and supporting authorities.
Explore counterarguments and examine where an argument may fail.
Examine factual and legal vulnerabilities that could change your strategy.
Consider next actions in the context of your argument and its risks.
Planned: distinguish a judgment’s ratio from facts, obiter, and procedural detail.
Planned: identify judgments that may conflict with the authorities supporting an argument.
The team
Our founders bring mathematical research and systems engineering together, with legal advisers helping connect the work to practice. Their credentials explain how the reasoning architecture is built.
Co-Founder (CEO)
Full-stack systems builder across automotive, media, medical imaging, and defence.
Math PhD, Princeton · IIT Bombay
Co-Founder (CSO)
Mathematician, ML engineer, and entrepreneur.
Math PhD, IISER Pune · IIT Madras · Cambridge ELLIS · TIFR postdoc
Founder
Math PhD, Princeton · IIT Bombay · INSA Young Scientist · Former Mathematics Department Chair, IISER Pune · Fellow of the Indian Academy of Sciences
Former District Judge, CJJD & JMFC
Senior legal adviser and mentor
LLM graduate and practising advocate
Legal adviser
We're testing the interface with a small cohort of corporate disputes counsel. Apply to join them and see Vidhan work on a real fact pattern.
Have questions about how Vidhan works, or whether it's for you?
Here's what you should know.
Vidhan is built for Indian corporate and commercial counsel exploring arguments and shaping legal strategy. It keeps professional judgment with the lawyer and makes the reasoning available for inspection.
Vidhan Atlas represents legal principles and argument structures mathematically. Mathematical algorithms explore how those structures connect with the facts of a matter. Language models have two restricted roles: converting small, bounded pieces of language into mathematical representations and orchestrating Vidhan's mathematical algorithms. Retrieval supplies authorities; the strategy is built by the mathematical reasoning core.
No. Vidhan's core reasoning uses mathematical algorithms. LLMs are restricted to converting small, bounded pieces of language into mathematical representations and orchestrating those algorithms; they are not asked to generate open-ended legal answers. This makes hallucinated outcomes highly unlikely, but “virtually zero” is not guaranteed zero. The practical issue is responsibility: Vidhan makes every material claim, source, and reasoning step easy to inspect, while the legal professional remains responsible for the work. See the Terms of Use.
Describe your practice and use case in general terms. Do not include client names, party details, privileged material, confidential facts, or documents. The application is not a place to submit a matter for analysis. Read the Privacy Policy before applying; questions about data handling can be sent to privacy@vidhan.ai.
The current focus is Indian corporate and commercial law. The coverage page lists the available legislation and the current boundaries for judgments and practice areas. Tell us your area of work in general terms so we can assess fit.
Early access provides full use of capabilities currently available during MVP testing, until testing ends or the agreed usage limit is reached, whichever comes first. Usage limits are communicated during onboarding, before you begin. There is no long-term commitment.
We ask you to be available for a 30-minute onboarding call within two weeks of being accepted, try the available capabilities, and share candid feedback. Your experience helps inform what we build next. We review each application for fit.
We review your application for fit and contact you about next steps. If you have a question before applying, contact founders@vidhan.ai.
Questions before applying? Contact the founders.
“I would rather create a precedent than find one.” — William O. Douglas, former U.S. Supreme Court Justice.
