The verification layer every AI transaction deserves.
No verification standard
LLM outputs are consumed daily in high-stakes contexts — medicine, law, government — with no standardized mechanism to prove what was asked, what was answered, or whether it was validated.
Attribution is invisible
When multi-agent AI systems produce a result, no layer currently tracks which agent contributed what. Responsibility is diffuse. Liability is undefined. Regulators have no handle on the process.
Learning without memory
AI systems optimize for individual sessions. Knowledge built through interaction is lost. Organizations re-teach systems constantly — without infrastructure for cumulative, attributed learning.
Four layers.
One integrated platform.
Attruvera is not a single tool — it is a vertically integrated trust infrastructure. Each layer is independently valuable; together they form the only complete solution for accountable AI deployment.
ALICE (Adaptive Learning Intelligence via Cognitive Engines) is a web-based knowledge platform that hosts structured bodies of work as graphs of linked units and attaches configurable AI agents to each unit. The foundation of the stack — free and open in its core form. Vela and the education configuration are the same software with different content profiles.
Max
When multiple AI agents collaborate on a task, Max coordinates their outputs — resolving conflicts, enforcing consistency, and producing a single harmonized result with a traceable decision record. No more contradiction between agents; no more opaque consensus.
Hudo
Hudo answers the question every regulated industry must be able to answer: who — or what — produced this output, and on what basis? A patent-pending attribution engine that binds AI outputs to their contributing agents, sources, and reasoning chains.
Vela
Vela is an invention-disclosure and portfolio-management service for technology-transfer offices, delivered as software as a service. Inventors submit disclosures through a guided form; the office reviews, tracks and manages the resulting portfolio. Vela is a configuration of the ALICE platform — the same software with a different content profile.
TVA
The cryptographic foundation of the entire stack. TVA creates an immutable, tamper-evident audit record of every AI interaction — what was asked, what was produced, what was verified — using a patent-pending hash-chain architecture. Think of it as the clearing and settlement layer for LLM transactions.
The clearing standard for AI.
Visa did not replace banks or payment networks. It became the trusted clearing layer between them — the standard that made transactions verifiable, accountable, and insurable at global scale.
Attruvera occupies the same position in the AI economy. We do not replace your LLM, your agents, or your applications. We become the layer that makes every interaction provable — and therefore deployable in regulated, high-stakes environments where trust is non-negotiable.
Attruvera Trust Infrastructure
Every AI transaction, verified.
Not a prototype. A track record.
U.S. State Health Agency
Attruvera technology was deployed through ISF, Inc. to analyze and optimize resource allocation for a U.S. state health agency — one of the largest algorithmic budget allocation exercises in state government. The system produced auditable, defensible recommendations at a scale no manual process could achieve.
ALICE at UTSA
ALICE (Adaptive Learning Intelligence via Cognitive Engines) is the Attruvera knowledge platform. In its education configuration, instructors author courses as linked lessons with learning objectives and rubrics, students submit work and converse with a course-scoped tutor, and instructors review AI-assisted feedback before release. Attruvera Technologies develops and operates ALICE; The University of Texas at San Antonio uses it in courses offered under university research pilots.
Open where it matters. Protected where it counts.
The core knowledge representation layer is open source — we believe the infrastructure of knowledge should be accessible. The attribution, harmonization, and verification layers that make AI trustworthy in regulated environments are licensed.
Built on mathematics. Grounded in accountability.
© 2026 · Attruvera Technologies, Inc. is a Delaware C-Corp · All rights reserved.
Attruvera Technologies is a deep-tech company incorporated in Delaware and headquartered in San Antonio, Texas. It is a research spinout of The University of Texas at San Antonio, emerging from the university's research enterprise in computational mathematics and AI governance. UTSA holds equity in the company under a conflict-of-interest management plan — a structure that reflects institutional confidence and ensures rigorous oversight of commercialization.
The company's foundational insight is mathematical: zero-error AI is provably impossible, which means the right question for any deployment is not "is this AI reliable?" but "is this AI's failure mode acceptable and visible?" Attruvera builds the infrastructure that makes failure modes visible — and therefore manageable.
Three conversations we want to have.
Seed Round
We are building the trust infrastructure layer for the AI economy. If you are investing in the governance, compliance, or accountability stack for enterprise AI, we should talk.
Strategic Partnerships
We work with system integrators, government contractors, and enterprise software vendors who need a credible, auditable AI accountability layer for their clients and deployments.
Technology Licensing
Whether you need Hudo, Max, TVA, or the full stack, our licensing team can scope a deployment that fits your regulatory environment, risk profile, and budget.