Frontier AI lab for verifiable intelligence
AI that
proves its work
AI that
proves its work
Current AI can generate fluent answers.
It cannot guarantee that those answers are correct.
Current AI can generate fluent answers.
It cannot guarantee that those answers are correct.
Pramaana builds the verification layer for AI: systems that turn complex human knowledge - tax codes, clinical guidelines, legal rules, safety constraints - into machine-checkable logic, so every answer can be traced, challenged, and proved.
Pramaana builds the verification layer for AI: systems that turn complex human knowledge - tax codes, clinical guidelines, legal rules, safety constraints - into machine-checkable logic, so every answer can be traced, challenged, and proved.
The verification problem
AI learned to sound right
before it learned to be right.
AI learned to sound right before it learned to be right.
Large language models are extraordinary at generating plausible answers. But in high-stakes domains, plausibility is not enough.
A tax position can turn on one exception.
A clinical recommendation can depend on one contraindication.
A legal conclusion can fail because one jurisdiction defines a term differently.
Today’s AI gives you an answer, maybe a citation, maybe a confidence score. But it rarely gives you what actually matters: a machine-checkable reason to believe it is correct.
Pillars
Pillars
RuleArena, an ACL 2025 benchmark, evaluates LLMs on real-world rule-guided reasoning across airline baggage rules, NBA transactions, and tax regulations; its authors report that LLMs struggle to identify and apply appropriate rules, make computation errors even after finding relevant rules, and generally perform poorly.
RuleArena, an ACL 2025 benchmark, evaluates LLMs on real-world rule-guided reasoning across airline baggage rules, NBA transactions, and tax regulations; its authors report that LLMs struggle to identify and apply appropriate rules, make computation errors even after finding relevant rules, and generally perform poorly.
arXiv
arXiv
Plausible is
not provable
Plausible is not provable
Plausible is not provable
A fluent explanation can still violate a rule, miss an exception, or apply the wrong constraint.
A fluent explanation can still violate a rule, miss an exception, or apply the wrong constraint.
Rules are not flat text
Rules are not flat text
Regulations, contracts, policies, and guidelines are systems of dependencies, exceptions, thresholds, and definitions.
Regulations, contracts, policies, and guidelines are systems of dependencies, exceptions, thresholds, and definitions.
Confidence is not accountability
Confidence is not accountability
A percentage cannot replace a proof. In high-stakes settings, “probably correct” is not an audit artifact.
A percentage cannot replace a proof. In high-stakes settings, “probably correct” is not an audit artifact.
Human review does not scale
Human review does not scale
When experts must redo the work to trust the model, AI has not removed the bottleneck. It has moved it.
When experts must redo the work to trust the model, AI has not removed the bottleneck. It has moved it.
Pramaana’s thesis
For high-stakes AI,
the output is not the Only answer.
The proof is.
The next frontier is not another chatbot with better wording. It is an AI system whose claims are constrained by formal representations of the world - and checked before they are trusted. A verifiable AI system should be able to show
The next frontier is not another chatbot with better wording. It is an AI system whose claims are constrained by formal representations of the world - and checked before they are trusted. A verifiable AI system should be able to show
what rule it used
what rule it used
what assumptions it made
what assumptions it made
what constraints it checked
what constraints it checked
where the answer follows
where the answer follows
where it fails
where it fails
The verification stack
From human knowledge to machine-checkable truth.
Pramaana builds domain-specific verification systems. We translate complex knowledge into formal representations, search the solution space with provers and solvers, and return proof artifacts that domain experts can inspect.
The result is AI with accountability built into the architecture - not added later through policy, prompting, or trust.
Leibniz
Panini
Ramanujan
Hardy
Domain Formalizer
Converts regulatory, statutory, policy, and scientific text into precise formal representations.
It captures definitions, conditions, exceptions, dependencies, and source traceability, so the system knows not just what a rule says, but where it applies.
Type System
Axioms
Sūtras
Operators
Boundaries
Input: natural-language rules
Output: machine-checkable specifications
The verification stack
From human knowledge to machine-checkable truth.
Pramaana builds domain-specific verification systems. We translate complex knowledge into formal representations, search the solution space with provers and solvers, and return proof artifacts that domain experts can inspect.
The result is AI with accountability built into the architecture - not added later through policy, prompting, or trust.
Leibniz
Panini
Ramanujan
Hardy
Domain Formalizer
Converts regulatory, statutory, policy, and scientific text into precise formal representations. It captures definitions, conditions, exceptions, dependencies, and source traceability, so the system knows not just what a rule says, but where it applies.
Type System
Axioms
Sūtras
Operators
Boundaries
Input: natural-language rules
Output: machine-checkable specifications
The verification stack
From human knowledge to machine-checkable truth.
Pramaana builds domain-specific verification systems. We translate complex knowledge into formal representations, search the solution space with provers and solvers, and return proof artifacts that domain experts can inspect.
The result is AI with accountability built into the architecture - not added later through policy, prompting, or trust.
Leibniz
Ramanujan
Panini
Hardy
Domain Formalizer
Converts regulatory, statutory, policy, and scientific text into precise formal representations. It captures definitions, conditions, exceptions, dependencies, and source traceability, so the system knows not just what a rule says, but where it applies.
Type System
Axioms
Sūtras
Operators
Boundaries
Input: natural-language rules
Output: machine-checkable specifications
Domains where Pramaana operates currently
Built for domains where a wrong answer actually matters.
Domains
Tax & statutory reasoning
Legal & regulatory compliance
Healthcare & clinical safety
Software, protocols & autonomous systems
Public systems & policy
Tax is structured, high-stakes, and full of exceptions. Pramaana’s first vertical focus is turning tax rules into verifiable systems for compliance, advisory, and policy simulation.
Use cases
taxability
nexus
exemptions
credits
statutory interpretation
policy simulation
Formal truth
accelerated trust
enabling power
Domains where Pramaana operates currently
Built for domains where a wrong answer actually matters.
Tax & statutory reasoning
Healthcare & clinical safety
Public systems & policy
Legal & regulatory compliance
Software, protocols & autonomous systems
Tax is structured, high-stakes, and full of exceptions. Pramaana’s first vertical focus is turning tax rules into verifiable systems for compliance, advisory, and policy simulation.
Use cases
taxability
nexus
exemptions
credits
statutory interpretation
policy simulation
Formal truth
accelerated trust
enabling power
Domains where Pramaana operates currently
Built for domains where a wrong answer actually matters.
Tax & statutory reasoning
Healthcare & clinical safety
Software, protocols & autonomous systems
Legal & regulatory compliance
Public systems & policy
Tax is structured, high-stakes, and full of exceptions. Pramaana’s first vertical focus is turning tax rules into verifiable systems for compliance, advisory, and policy simulation.
Use cases
taxability
nexus
exemptions
credits
statutory interpretation
policy simulation
Formal truth
accelerated trust
enabling power
The world's
hardest problems are
not unsolvable.
They are unformalized.
research partnership
If the domain has rules, constraints, and consequences,
it can be formalized.
If the domain has rules, constraints, and consequences,
it can be formalized.
If the domain has rules, constraints, and consequences,
it can be formalized.
The knowledge already exists.
It lives in codes, case law, guidelines, standards, papers, protocols, and expert practice. But it is written for humans to interpret - not for machines to verify. Pramaana’s work is to make that knowledge executable, inspectable, and provable.
The knowledge already exists.
It lives in codes, case law, guidelines, standards, papers, protocols, and expert practice. But it is written for humans to interpret - not for machines to verify. Pramaana’s work is to make that knowledge executable, inspectable, and provable.
The knowledge already exists.
It lives in codes, case law, guidelines, standards, papers, protocols, and expert practice. But it is written for humans to interpret - not for machines to verify. Pramaana’s work is to make that knowledge executable, inspectable, and provable.
research partnership
Formalizing the world’s knowledge.
TEAM
meet experts behind the innovation
TEAM
meet experts
behind the innovation
TEAM
meet experts
behind the innovation
Pramanpatra
Pramaanpatra
Get research notes, essays, benchmarks, and field reports on AI verification, formal methods, autoformalization, and the domains being rebuilt around machine-checkable truth.
No hype cycle recap.
Just the work.
The verification stack
From human knowledge to machine-checkable truth.
From human knowledge to machine-checkable truth.
Pramaana builds domain-specific verification systems. We translate complex knowledge into formal representations, search the solution space with provers and solvers, and return proof artifacts that domain experts can inspect.
Pramaana builds domain-specific verification systems. We translate complex knowledge into formal representations, search the solution space with provers and solvers, and return proof artifacts that domain experts can inspect.
The result is AI with accountability built into the architecture - not added later through policy, prompting, or trust.
The result is AI with accountability built into the architecture - not added later through policy, prompting, or trust.
An inaugural cohort for researchers working on formalizing high-stakes domains.
What we support
What we support
Computational law, regulatory compliance, autonomous safety, financial protocols, clinical reasoning, scientific theories, and AI-generated code correctness. Did we miss anything?
What fellows receive
What fellows receive
Funding, platform credits, compute, and a dedicated Pramaana engineer embedded with the project.
What we want
What we want
Problems with rules, constraints, ambiguity, and consequences - the kind of domains where proof changes what is possible.