AI you can verify.
Knowledge you can trust.

AI you can verify. Knowledge you can trust.

Trusted AI for enterprise knowledge, neurosymbolically validated,
peer-reviewed, sovereign by design.

We are accelerating the advent of General AI through cutting-edge neuro-symbolic research.

The Pain

EnterpriseAIhasatrustproblem.
MostenterpriseAInevermakesitpastthepilot.Notbecausethetechnologydoesn'twork,butbecauseitcan'tproveitdoes.
Modelsthatsoundconfidentwhilecitingsourcesthatdon'texist.Outputsthatchangebetweenidenticalqueries.Audittrailsthatcan'tbereconstructed.Complianceteamsthatwon'tsignoffonwhattheycan'tverify.
Inregulatedindustries,"probablyright"isnotafeature.It'saliability.
EnterpriseAIhasatrustproblem.
MostenterpriseAInevermakesitpastthepilot.Notbecausethetechnologydoesn'twork,butbecauseitcan'tproveitdoes.
Modelsthatsoundconfidentwhilecitingsourcesthatdon'texist.Outputsthatchangebetweenidenticalqueries.Audittrailsthatcan'tbereconstructed.Complianceteamsthatwon'tsignoffonwhattheycan'tverify.
Inregulatedindustries,"probablyright"isnotafeature.It'saliability.

OUR SOLUTION

WebuiltAIthatprovesitswork
WebuiltAIthatprovesitswork

Published
Research

Published Research

Open-sourced

Open Sourced

Independently Verifiable

Independently Verifiable

ExtensityAIisaneurosymbolicstackdesignedforenvironmentswhereeveryanswerhastobedefensible,notafterthefact,butbyconstruction.
Wecombinelargelanguagemodelswithsymbolicvalidation,knowledgegraphreasoning,andcontract-controlledoutputs.Everyretrieval,everysynthesis,everyclaimcanbetracedbacktoitssourceandverifiedagainstyourdata.
ExtensityAIisaneurosymbolicstackdesignedforenvironmentswhereeveryanswerhastobedefensible,notafterthefact,butbyconstruction.
Wecombinelargelanguagemodelswithsymbolicvalidation,knowledgegraphreasoning,andcontract-controlledoutputs.Everyretrieval,everysynthesis,everyclaimcanbetracedbacktoitssourceandverifiedagainstyourdata.

the Four Pillars

Built different. On purpose.

Trusted & Verifiable

Every answer traceable back to its source

Outputs are validated against semantic and type conditions before they leave the stack. No invented citations. No silent failures.

Deep Knowledge Retrieval

Find, synthesize, and ground answers in your own data

Vector retrieval combined with symbolic constraints and knowledge graph traversal. Built for production scale on enterprise document volumes.

Deep Knowledge Retrieval

Find, synthesize, and ground answers in your own data

Vector retrieval combined with symbolic constraints and knowledge graph traversal. Built for production scale on enterprise document volumes.

Neurosymbolic
by Design

Neurosymbolic by Design

LLM + knowledge graph + symbolic validation, no guessing layer.

The probabilistic strength of language models, controlled by symbolic logic. Reasoning you can inspect, not just observe.

Neurosymbolic by Design

LLM + knowledge graph + symbolic validation, no guessing layer.

The probabilistic strength of language models, controlled by symbolic logic. Reasoning you can inspect, not just observe.

Sovereign &
On-Premise

Your data never leaves your infrastructure

Deploy on your hardware, behind your firewall, under your control. Including the model weights. No vendor lock-in. No third-party API dependency.

Sovereign & On-Premise

Your data never leaves your infrastructure

Deploy on your hardware, behind your firewall, under your control. Including the model weights. No vendor lock-in. No third-party API dependency.

How it works

From question to verified answer

Step 1

Step 2

Step 3

Step 4

01

Retrieve

Symbolic and vector retrieval against your data — across documents, databases, and structured knowledge.

02

Reason

Language model synthesis under contract constraints — semantic and type requirements enforced at every step.

03

Validate

Symbolic verification of the output against your domain rules — before it reaches the user.

04

Trace

Full provenance: every claim mapped back to the source passage, the retrieval path, the validation result.

01

Retrieve

Symbolic and vector retrieval against your data — across documents, databases, and structured knowledge.

02

Reason

Language model synthesis under contract constraints — semantic and type requirements enforced at every step.

03

Validate

Symbolic verification of the output against your domain rules — before it reaches the user.

04

Trace

Full provenance: every claim mapped back to the source passage, the retrieval path, the validation result.

Use cases

Built for regulated enterprises

Legal & Notaries

Document binding, contract analysis, and verifiable case research

Legal & Notaries

Document binding, contract analysis, and verifiable case research

Finance & Controlling

Reporting, regulatory filings, and audit-grade document synthesis.

Finance & Controlling

Reporting, regulatory filings, and audit-grade document synthesis.

Public Sector

Administrative processes with sovereignty and traceability requirements.

Public Sector

Administrative processes with sovereignty and traceability requirements.

Digital Transformation

AI strategy and trustworthy knowledge infrastructure for the enterprise.

Digital Transformation

AI strategy and trustworthy knowledge infrastructure for the enterprise.

Consulting

Deep research and synthesis for advisory work — grounded in client data.

Consulting

Deep research and synthesis for advisory work — grounded in client data.

Substance

Engineered for environments
that can't afford to guess

No logos. No promises. Just architecture and research you can verify yourself.

  • ON-PREMISE

LLM

Symbolic

Validation

Knowledge

Graph

  • ON-PREMISE

LLM

Symbolic

Validation

Knowledge

Graph

No data leaves your infrastructure

Every answer source-traceable

EU AI Act Annex IV-aligned

Research

Our research is public. Read it yourself.

From foundational theory to working code, every layer of our stack is published or open-sourced.

Trustworthy Agent Design

Trustworthy Agent Design

A practical whitepaper on designing trustworthy LLM agents with contract-based controls that validate inputs, outputs, and semantic requirements before agents act.

HyDRA - Knowledge Graph Construction

HyDRA - Knowledge Graph Construction

A whitepaper on HyDRA, a hybrid-driven reasoning architecture that uses collaborative agents, competency questions, and verifiable contracts to automate reliable knowledge graph construction.

SymbolicAI Framework (Open Source)

SymbolicAI Framework (Open Source)

A developer-focused whitepaper on SymbolicAI, the open-source neurosymbolic framework for composing LLMs with Python-native symbolic abstractions, semantic primitives, and contract validation.

Full publication list available on request.

Ready for AI you can defend?

Let's talk about your knowledge stack, what you're trying to build,what's blocking you, and whether our approach fits.

Ready for AI you can defend?

Let's talk about your knowledge stack, what you're trying to build,what's blocking you, and whether our approach fits.