QNFO Unified License Agreement v2.0

Effective: May 29, 2026 · SPDX: LicenseRef-QNFO-ULA-2.0 · QNFO Hub

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QNFO Unified License Agreement (QNFO-ULA) — Version 2.0

Effective Date: May 29, 2026
Supersedes: QNFO Content License Agreement v1.1, AI System License Agreement (ASLA), all CC license variants previously applied, and all project-specific licenses across the QNFO and QWAV portfolios.
Licensor: Rowan Brad Quni-Gudzinas (ORCID: 0009-0002-4317-5604, ISNI: 0000 0005 2645 6062)
SPDX Identifier: LicenseRef-QNFO-ULA-2.0
Scope: All Content across the QNFO and QWAV ecosystems — all projects, repositories, files, documents, data, code, publications, websites, prompts, configurations, theories, diagrams, and intellectual property of every kind and in every medium, however distributed, now existing and hereafter created. This Agreement applies in perpetuity to all such Content unless and until superseded by a subsequent version of this Agreement issued by Licensor.

Short reference: This Content is licensed under the QNFO Unified License Agreement v2.0 (CC BY-NC-SA 4.0 + QNFO Supplemental Terms).
Full text: https://qnfo.org/legal/license | https://qwav.tech/legal/license

Preamble — Values and Purpose

This License is founded on the following principles:

The QNFO and QWAV ecosystems — encompassing all projects, code, documentation, data, theories, publications, websites, prompts, AI systems, configurations, diagrams, datasets, and associated materials under the QNFO, QWAV, q08, and related namespaces (collectively, the "Content") — are provided primarily for non-commercial research, education, and activities that promote social good and ethical innovation. Commercial use may be permitted under a separate agreement where it demonstrably serves the public good (see Section 10.7).

1. License Grant

1.1 Base License — Creative Commons

This Content is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0).

Full text: https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode

1.2 Supplemental Terms — QNFO Supplemental Terms

In addition to CC BY-NC-SA 4.0, this Content is subject to the supplemental terms in Sections 2–10 below (the "Supplemental Terms"). The CC BY-NC-SA 4.0 license and the Supplemental Terms together form the QNFO Unified License Agreement ("this Agreement"). They shall be read and enforced as a single, integrated agreement. In the event of any conflict between CC BY-NC-SA 4.0 and the Supplemental Terms, the Supplemental Terms shall prevail.

1.3 Scope — Universal Application

This Agreement applies to all Content across the QNFO and QWAV ecosystems, including but not limited to:

This Agreement applies to such Content in perpetuity, from the date of its creation or from the effective date of this Agreement (whichever is later), unless and until superseded by a subsequent version of this Agreement issued by Licensor.

Binding on Access: This Agreement is binding on any person or entity that accesses, downloads, copies, or otherwise uses the Content. By accessing the Content through any means (including but not limited to web browsing, API access, direct download, or automated retrieval), You acknowledge that You have been given notice of this Agreement and agree to be bound by its terms. The publication of this Agreement alongside the Content, on websites where the Content is available, and in metadata associated with the Content constitutes sufficient notice to bind any user of the Content to these terms. This provision is intended to establish a binding contract with any user of the Content and to defeat any defense based on "browsewrap," lack of privity, absence of affirmative acceptance, or similar doctrines. If You do not agree to these terms, You must immediately cease all access to and use of the Content. Your continued access to or use of the Content constitutes acceptance of this Agreement.

1.4 Database Rights

This Agreement covers all rights in the Content, including but not limited to copyright, sui generis database rights (as defined in Directive 96/9/EC of the European Parliament and of the Council of 11 March 1996 on the legal protection of databases, as amended and/or succeeded, as well as other essentially equivalent rights anywhere in the world), and any other intellectual property rights held by Licensor. The extraction and/or re-utilization of the whole or a substantial part of the contents of any database constituting Content is subject to the terms of this Agreement.

1.5 Publication Exception — Licensor-Designated Public Content

Notwithstanding any other provision of this Agreement, Licensor may, at Licensor's sole discretion, designate specific Content as "Public Content" subject to more permissive terms. Public Content shall be clearly marked as such through: (a) a prominent notice in the Content itself (e.g., "Licensed under CC BY 4.0 as QNFO Public Content"); (b) a separate license file or metadata accompanying the Content; or (c) publication on a QNFO website or platform with a clear designation of public content status.

Public Content is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0) only, without the QNFO Supplemental Terms. All other Content remains governed by this full Agreement.

The following types of Content are presumptively eligible for designation as Public Content: research papers, preprints, and academic publications; blog posts, articles, and public-facing educational materials; conference presentations, posters, and talk materials; high-level concept descriptions, white papers, and vision documents; press releases, announcements, and public communications; and educational tutorials and documentation intended for broad public dissemination.

The following types of Content are presumptively NOT eligible for Public Content designation (and remain governed by the full Agreement): source code, software, and production implementations; detailed technical specifications, formalisms, and algorithms; training data, model weights, and production AI/ML artifacts; internal development documentation and agent configurations; datasets and databases intended for research or commercial use; and prompt templates and AI system instructions.

Licensor may designate Public Content at any time, may revoke such designation for future versions of the Content (but not retroactively for copies already distributed in accordance with this Section), and may establish additional criteria for Public Content designation at Licensor's discretion. The absence of a Public Content designation on any particular Content shall mean such Content is governed by the full terms of this Agreement. This Section 1.5 does not create any obligation for Licensor to designate any Content as Public Content, nor does it create any expectation or entitlement to such designation.

The existence of the Publication Exception does not alter or waive any rights under this Agreement with respect to non-Public Content. Nothing in this Section shall be construed as a dedication of any Content to the public domain or as a waiver of any intellectual property rights except as explicitly stated.

2. Permitted Uses

Subject to the terms herein, You are encouraged to use the Content for:

2.1 Non-Commercial Use Requirement — With Search and Discovery Exception

You may not use the Content for commercial purposes. "Commercial purposes" include, but are not limited to:

Search and Discovery Exception: Notwithstanding the foregoing prohibitions on automated access, the following activities are expressly permitted and do not constitute prohibited commercial use under this Section, provided they comply with QNFO's technical access policies (including robots.txt directives, rate limits, and API terms where applicable):

(a) General-Purpose Search Engine Indexing: Automated crawling, indexing, and caching of publicly accessible Content by general-purpose search engines (including but not limited to Google, Bing, DuckDuckGo, Yandex, Baidu, and similar services) for the purpose of providing search results, snippets, and cached copies to users. Search engines may display short excerpts ("snippets") of Content in search results without this constituting commercial reproduction.

(b) Academic and Scientific Discovery Indexing: Automated crawling and indexing of Content by academic search engines, citation databases, and research discovery platforms (including but not limited to Google Scholar, Semantic Scholar, arXiv, PubMed, Crossref, OpenAlex, Dimensions, Web of Science, Scopus, and similar services) for the purpose of academic citation, indexing, and research discovery. Such services may index metadata, abstracts, and citations from the Content.

(c) Web Archiving and Digital Preservation: Automated crawling and archiving of publicly accessible Content by non-profit digital preservation and archiving services (including but not limited to the Internet Archive's Wayback Machine, national library archiving programs, academic institutional repositories, and similar preservation services) for the purpose of historical preservation and public access to archived content.

(d) AI-Powered Search and Retrieval Services: Automated indexing and retrieval of Content by AI-powered search, question-answering, and information retrieval services (including but not limited to Perplexity, You.com, ChatGPT Search, Google AI Overviews, Bing Copilot, and similar services) for the purpose of providing search results, summaries, answers, or citations to users — provided that:
1. The service's primary function is search, retrieval, or question-answering (not foundational model training);
2. The service provides attribution or citation to QNFO as the source of the Content;
3. The service does not use the Content to train, fine-tune, or improve the underlying foundational AI model itself (as distinct from indexing for retrieval);
4. The service provides a mechanism for QNFO to opt out of indexing (such as robots.txt compliance or a dedicated opt-out process).

(e) RSS Feeds, News Aggregators, and Content Syndication: Automated retrieval of Content via RSS feeds, Atom feeds, and similar syndication formats for the purpose of content aggregation, news reading, and personal or organizational information management.

(f) Accessibility and Assistive Technology: Automated access to Content for the purpose of making it accessible to persons with disabilities, including but not limited to screen readers, text-to-speech engines, and accessibility auditing tools.

The distinction is: indexing Content to help people FIND it (permitted) vs. extracting Content to TRAIN models that replace or compete with it (prohibited). Services that index for discovery and provide proper attribution operate within this Exception. Services that extract for training foundational models, compiling commercial datasets, or building products that substitute for the Content do not.

Technical Implementation: QNFO and QWAV websites and platforms will maintain robots.txt files and similar technical access controls that:
- Permit crawling by legitimate search engines, academic indexers, and archival services identified in subsections (a)-(f) above;
- Restrict crawling by AI training bots, commercial data harvesters, and other automated systems not covered by this Exception;
- May implement rate limiting, CAPTCHA challenges, and API authentication to prevent abuse while permitting legitimate discovery access.

Non-Profit Research Exception: Non-profit research organizations that compile datasets for academic research purposes (with appropriate attribution and non-commercial terms) are not engaged in prohibited commercial use under this Section.

For clarity: public-good activities that incidentally generate revenue (e.g., a university charging tuition that includes QNFO materials in coursework) are not prohibited commercial use, provided the Content itself is not the primary revenue-generating component.

Fair Use Waiver for AI/ML Training: To the maximum extent permitted by applicable law, You waive any defense of fair use, fair dealing, text and data mining exception, temporary reproduction exception, incidental inclusion, or similar limitation or exception to copyright or database rights under any applicable law (including but not limited to 17 U.S.C. § 107, Article 5(5) of the EU Copyright Directive 2001/29/EC, Articles 3 and 4 of the EU Digital Single Market Directive 2019/790, and equivalent provisions in other jurisdictions) with respect to the extraction, reproduction, or use of the Content for the purpose of training, fine-tuning, or developing artificial intelligence or machine learning models, systems, or services. This waiver is a material term of this Agreement.

Clarification — AI Research to Commercial Transition: For AI/ML contexts specifically: training, fine-tuning, or developing a model, system, or service is "commercial" if the model, system, or service, or any derivative thereof, is or will be: (a) offered as a paid service or product; (b) used to generate revenue (including through advertising, subscription, or API access fees); (c) developed by or for a for-profit entity; (d) used in connection with any commercial product, service, or business operation; or (e) released under terms that permit commercial use by downstream users. If a model is developed for non-commercial research but is subsequently commercialized (including through acquisition, licensing, change of use, or corporate reorganization), such commercialization constitutes a breach of this Agreement dating back to the initial training if the training was not separately authorized under Section 10.7. Researchers and organizations intending potential future commercialization should contact Licensor under Section 10.7 before commencing training.

2.2 Prohibited Uses — AI and Behavioral Restrictions (RAIL-Inspired)

In addition to the general non-commercial requirement, the following specific uses of the Content are expressly prohibited regardless of whether they are characterized as commercial or non-commercial:

(a) Surveillance and Profiling: You may not use the Content to develop, train, or operate systems for mass surveillance, predictive policing, criminal justice profiling, or any system that makes automated decisions affecting individuals' legal rights, access to services, or fundamental freedoms — except where such use is for academic research with appropriate ethics board approval and does not result in deployment.

(b) Disinformation and Manipulation: You may not use the Content to generate or disseminate disinformation at scale, to engage in mass psychological manipulation, to operate social media bots or coordinated inauthentic behavior networks, or to develop systems designed to deceive, manipulate, or exploit vulnerable populations.

(c) Autonomous Weapons and Military Applications: You may not use the Content in autonomous weapons systems, in systems designed to cause physical harm to persons, or in military applications that violate international humanitarian law, including the Geneva Conventions and their Additional Protocols.

(d) Exploitative Behavioral Engineering: You may not use the Content to develop systems designed to exploit psychological vulnerabilities, to promote addictive behaviors for commercial gain, or to manipulate human behavior in ways that undermine individual autonomy and dignity.

(e) AI Training for Commercial Models Without Public Benefit Agreement: You may not use the Content to train, fine-tune, or otherwise develop artificial intelligence or machine learning models, systems, or services where the primary purpose or effect is commercial gain, unless You have entered into a separate written agreement with Licensor under Section 10.7 that includes demonstrable public benefit commitments.

2.3 Exploitation and Hoarding — Statement of Principle

This Agreement is intended to prevent the exploitation, enclosure, and hoarding of the Content for private profit without commensurate public benefit. Uses that extract value from the Content while contributing nothing back to the commons — whether through proprietary enclosure, paywalled access, or AI training for purely commercial models — are contrary to the purpose of this Agreement and are prohibited. The fact that a use may be technically "non-commercial" in a narrow sense does not exempt it from this principle if its effect is to appropriate the Content's value for private gain while denying its benefits to the public.

2.4 Edge Case Clarifications — What "Commercial" Means in Practice

To provide clear guidance, the following specific scenarios are addressed:

(a) Non-Profit Organizations: A registered non-profit, charitable, or educational organization's use of the Content in furtherance of its charitable or educational mission is not commercial use, even if the organization generates revenue (e.g., grants, donations, membership fees, conference registration), provided the Content itself is not sold, licensed, or used as the primary value proposition in a revenue-generating activity. However, if a non-profit organization uses the Content to develop a product or service that it sells or licenses for profit (including through a for-profit subsidiary), such use is commercial.

(b) Government Entities: Use by government entities for public administration, public education, public research, or public service delivery is not commercial use. Use by government entities in connection with commercial activities (e.g., government-owned enterprises operating in competitive markets, or government licensing of technology to private entities for royalties) may constitute commercial use depending on the specific circumstances.

(c) Individual Consultants and Freelancers: An individual providing consulting, advisory, or freelance services who uses knowledge gained from the Content (but does not reproduce, distribute, or incorporate the Content itself into deliverables) is not engaged in commercial use of the Content. However, reproducing, distributing, or incorporating substantial portions of the Content into client deliverables for which the consultant is paid constitutes commercial use.

(d) Academic Publishers: A commercial academic publisher (including but not limited to Elsevier, Springer Nature, Taylor & Francis, Wiley, and similar entities) that publishes a work incorporating the Content behind a paywall, or charges subscription or access fees for such work, is engaged in commercial use and requires a separate commercial license under Section 10.7. Open-access publication (including gold open access with article processing charges paid by authors or institutions, where the published work is freely accessible to the public) is not prohibited commercial use, provided attribution is given and the work is licensed under a ShareAlike-compatible license.

(e) Open Source Projects: An open source project that accepts donations, sponsorships, or grants to support its development is not engaged in commercial use of the Content, provided the project itself does not sell, license, or otherwise commercialize the Content. However, if the open source project offers a commercial license, paid support, or proprietary add-ons that incorporate the Content, such use is commercial.

(f) Social Media and Content Platforms: Posting, sharing, or discussing the Content (or excerpts thereof) on social media platforms, blogs, forums, or similar platforms for purposes of commentary, criticism, education, or news reporting is not commercial use, even if the platform itself is commercial, provided the posting individual or entity is not directly monetizing the Content (e.g., through paid access, subscription content, or advertising directly tied to the Content).

(g) Internal Business Use: Use of the Content by a for-profit entity for its internal operations (including but not limited to employee training, internal research and development, or process improvement) constitutes commercial use and is prohibited without a separate commercial license under Section 10.7. The fact that the Content is not directly resold does not make internal business use non-commercial.

Principle for unresolved cases: In any scenario not explicitly addressed above, the determination of whether a use is "commercial" shall be guided by the principle stated in Section 2.3: does the use extract value from the Content for private gain without commensurate public benefit? If so, it is commercial use prohibited by this Agreement.

2.5 Technical Protection Measures — Anti-Circumvention

Licensor may implement technical protection measures (including but not limited to robots.txt directives, rate limiting, CAPTCHA challenges, API authentication requirements, cryptographic content signing, and digital watermarking) to protect the Content from unauthorized access or use.

Circumvention of such technical protection measures for the purpose of accessing or using the Content in a manner prohibited by this Agreement may constitute a violation of anti-circumvention laws, including but not limited to 17 U.S.C. § 1201 in the United States, Article 6 of the EU Copyright Directive 2001/29/EC, Sections 296-296ZF of the UK Copyright, Designs and Patents Act 1988, and equivalent legislation in other jurisdictions. Such circumvention may give rise to liability independently of any breach of this Agreement.

The implementation or non-implementation of technical protection measures by Licensor does not alter, expand, or limit the rights and obligations under this Agreement. Licensor's failure to implement technical protection measures shall not constitute a waiver of any rights under this Agreement, nor shall it create any implied license, estoppel, or defense based on the accessibility of the Content.

Where Licensor implements anti-scraping technical measures, any entity that bypasses, circumvents, or disables such measures to access the Content for purposes prohibited by this Agreement (including but not limited to AI/ML training, commercial dataset compilation, or unauthorized commercial use) shall be deemed to have knowingly violated this Agreement and applicable anti-circumvention laws.

3. Attribution Requirements

3.1 Standard Attribution

If You use, adapt, or refer to the Content in any published or publicly shared work (including but not limited to academic papers, articles, books, presentations, software, websites, patents, technical reports, AI model documentation, and dataset descriptions), You must clearly attribute it. Include a statement substantially similar to:

"This work incorporates or builds upon material from the QNFO/QWAV ecosystem (Rowan Brad Quni-Gudzinas, ORCID: 0009-0002-4317-5604), available under the QNFO Unified License Agreement v2.0 at https://qnfo.org/legal/license."

For code and software, include the following header in each source file:

SPDX-License-Identifier: LicenseRef-QNFO-ULA-2.0
Copyright (c) [YEAR] Rowan Brad Quni-Gudzinas
Licensed under the QNFO Unified License Agreement v2.0
(CC BY-NC-SA 4.0 + QNFO Supplemental Terms)
Full text: https://qnfo.org/legal/license

3.2 Indication of Changes

If You modify the Content when creating a derivative work, You must include a statement indicating that changes were made to the original Content.

3.3 AI Model Documentation

If You use the Content in the training, development, or fine-tuning of any AI or machine learning model (whether permitted under this Agreement or under a separate agreement pursuant to Section 10.7), You must disclose such use in the model's documentation, technical report, or model card, and cite the Content as a training data source in accordance with Section 3.1.

4. ShareAlike — Copyleft Requirement

4.1 ShareAlike Propagation

The ShareAlike requirement of CC BY-NC-SA 4.0 applies to the Content and all derivative works. If You remix, transform, or build upon the Content, You must distribute Your contributions under the same license terms — specifically, CC BY-NC-SA 4.0, this Agreement (QNFO-ULA v2.0), or a Creative Commons Compatible License as defined by Creative Commons.

4.2 License Compatibility

For purposes of the ShareAlike requirement, CC BY-NC-SA 4.0 alone (without the QNFO Supplemental Terms in Sections 2–10 of this Agreement) is considered a compatible license. This means that if You create a derivative work and license it under CC BY-NC-SA 4.0 (without the QNFO Supplemental Terms), You have satisfied the ShareAlike requirement. However:

4.3 No Additional Restrictions

In accordance with CC BY-NC-SA 4.0, You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.

5. Patent Prior Art Citation — CRITICAL TERM

5.1 Mandatory Disclosure

If You, or any entity You represent, develop any invention or file any patent application anywhere in the world that was influenced by, incorporates, or is derived from the Content, You must explicitly cite QNFO / QWAV (Rowan Brad Quni-Gudzinas, ORCID: 0009-0002-4317-5604) as prior art in the patent application, in all related documentation, and in any Information Disclosure Statement (IDS) or equivalent filing required by the relevant patent office.

Failure to disclose known prior art can affect patent validity under various national and international laws, including but not limited to:

Compliance with this clause is a material term of this Agreement. Failure to comply constitutes both a breach of this Agreement and may independently affect the validity or enforceability of any resulting patent under the applicable laws cited above.

6. Breach and Consequences

6.1 Unauthorized Commercial Use — Liquidated Damages

If You breach Section 2.1 by using the Content for commercial purposes (including but not limited to AI/ML training for commercial models as specified in Section 2.1), You agree that actual damages would be extremely difficult or impossible to quantify given the unique, non-fungible nature of intellectual property, the speculative character of commercial applications, the difficulty of tracing causal contributions, and the potential for rapid, global dissemination.

Therefore, You agree to pay Licensor liquidated damages equal to eighty-five percent (85%) of all gross revenue, economic value, or financial benefit derived directly or indirectly from such unauthorized commercial use. This amount is agreed upon as a reasonable pre-estimate of the damages incurred by Licensor due to the breach of the non-commercial terms, not as a penalty. The liquidated damages shall be calculated based on gross revenue, market value of equity received, cost savings realized, or other economic benefits obtained, without deduction for costs, expenses, taxes, or overhead.

For the avoidance of doubt: "gross revenue" includes, but is not limited to, subscription fees, advertising revenue, data licensing fees, API access fees, consulting fees, acquisition prices, investment valuations attributable to the Content, and the market value of any non-monetary consideration received. In the case of AI/ML training violations, "economic benefit" includes the increase in valuation, revenue, or market position attributable to models trained on the Content.

Fallback Provision: If a court or arbitral tribunal of competent jurisdiction finds the liquidated damages amount specified in this Section to be unenforceable as a penalty, excessive, or otherwise contrary to applicable law (including but not limited to Article 163(3) of the Swiss Code of Obligations), the parties agree that Licensor shall be entitled to recover: (a) the highest amount of liquidated damages that such court or tribunal finds enforceable under applicable law, not to exceed eighty-five percent (85%) of gross revenue; or (b) at Licensor's election, actual damages (including statutory damages where available under applicable copyright law, such as 17 U.S.C. § 504 in the United States or equivalent provisions in other jurisdictions), the profits of the infringer attributable to the infringement, and Licensor's reasonable attorneys' fees, expert costs, and investigation costs. Licensor's election under this fallback provision shall be made in writing and may be changed at any time before final judgment or award. The availability of this fallback provision does not constitute an admission that the primary liquidated damages provision is unenforceable, and Licensor shall be entitled to argue for the full enforceability of the primary provision in any proceeding.

6.2 Patent Misuse Consequences

Failure to comply with the prior art citation requirement in Section 5 constitutes a material breach of this Agreement. In addition to potential impacts on patent validity under applicable law (including but not limited to findings of inequitable conduct rendering patents unenforceable), Licensor reserves the right to pursue remedies for breach of contract, which may include damages, legal costs, and injunctive relief.

6.3 AI/ML Training Violations — Specific Consequences

In addition to the liquidated damages provided in Section 6.1, any entity that uses the Content for AI/ML training in violation of Section 2.1 or Section 2.2(e) shall, upon Licensor's request:

6.4 License Termination

This license and the permissions granted herein will terminate automatically upon any breach by You of these terms. Upon termination, You must immediately cease all use of the Content and destroy any copies or derivative works in Your possession or control. Termination does not affect Licensor's right to recover damages for breaches occurring prior to termination.

6.5 Enforcement

Licensor reserves the right to pursue all available legal and equitable remedies to enforce these terms, including injunctive relief, specific performance, and recovery of attorneys' fees and costs. The rights and remedies provided in this Agreement are cumulative and not exclusive of any rights or remedies provided by law.

6.6 Platform and Marketplace Enforcement

In addition to legal remedies, Licensor may pursue platform-level enforcement actions against unauthorized commercial use of the Content, including but not limited to:

(a) DMCA and Equivalent Takedown Notices: Licensor may issue takedown notices under the Digital Millennium Copyright Act (17 U.S.C. § 512) or equivalent legislation in other jurisdictions (e.g., EU Directive 2000/31/EC, UK Copyright, Designs and Patents Act 1988 s. 97A, Canada's Copyright Modernization Act) to remove infringing Content from websites, platforms, and services.

(b) AI Model Marketplace Removal Requests: Licensor may request the removal or delisting of AI models, datasets, or model weights from platforms including but not limited to Hugging Face, GitHub, GitLab, Kaggle, and similar model-sharing and dataset-sharing platforms, where such models or datasets were trained on or incorporate the Content in violation of this Agreement.

(c) Code Repository Takedown Requests: Licensor may request the removal of repositories, forks, or code from GitHub, GitLab, Bitbucket, or similar platforms where such repositories contain the Content used in violation of this Agreement.

(d) Dataset Registry Delisting: Licensor may request delisting from dataset registries, catalogs, and search engines (including but not limited to Google Dataset Search, Papers with Code, and similar services) of datasets compiled in violation of this Agreement.

(e) Search Engine Deindexing: Licensor may submit requests to search engines (including but not limited to Google, Bing) under applicable laws and policies to deindex pages that host the Content in violation of this Agreement.

(f) Domain and Hosting Provider Complaints: Licensor may file complaints with domain registrars, hosting providers, and content delivery networks regarding websites that systematically violate this Agreement.

(g) Platform Terms of Service Enforcement: Licensor may report violations to platforms under their own terms of service, acceptable use policies, or community guidelines, where such platforms prohibit copyright infringement or unauthorized content use.

The availability of platform-level enforcement does not limit or replace Licensor's right to pursue legal remedies under Sections 6.1–6.5. Licensor may pursue platform and legal remedies simultaneously or sequentially at Licensor's sole discretion.

7. Intellectual Property Ownership

7.1 Licensor Identity

For the purposes of this Agreement, the "Licensor" is Rowan Brad Quni-Gudzinas (ORCID: 0009-0002-4317-5604, ISNI: 0000 0005 2645 6062).

7.2 Name Clarification

For avoidance of doubt, Licensor Rowan Brad Quni-Gudzinas was previously known legally and professionally as Bradley James Gudzinas. Intellectual property related to or forming part of the Content (including but not limited to copyrights, patents, trademarks, and database rights) may exist or have been filed under either name or variations thereof. All such intellectual property is Licensor's, regardless of the name under which it was originally created, registered, or filed.

7.3 QNFO and QWAV — Organizational Identity

QNFO ("QNFO," "Quniverse") and QWAV ("Quantum Harmonic Resonance Wave Computing") are the primary organizational and platform identities under which Licensor creates and distributes the Content. References in this Agreement to "QNFO," "QWAV," or "QNFO/QWAV" all refer to Content owned by Licensor Rowan Brad Quni-Gudzinas and distributed under these names.

7.4 Ownership Retention

Licensor retains all ownership rights, title, and interest, including copyright, patent, trademark, database rights, and other intellectual property rights, in and to the Content, regardless of the name under which such rights were originally secured or filed.

7.5 License Grant Only

This Agreement grants You limited permission to use the Content as specified herein; it does not transfer any ownership rights to You. No license, immunity, or other right is granted under any patent, trademark, trade secret, or other intellectual property right of Licensor, except as expressly provided in this Agreement.

8. International Governance — Governing Law and Dispute Resolution

8.1 Governing Law

This Agreement shall be governed by and construed in accordance with the substantive laws of Switzerland, without regard to its conflict of law principles. Switzerland is chosen as a neutral, internationally respected jurisdiction with a strong tradition of intellectual property protection, situated outside the direct legal spheres of major technology powers, and equally accessible to parties from all regions.

8.2 Dispute Resolution — Binding International Arbitration

Any dispute, controversy, or claim arising out of or relating to this Agreement, including its breach, termination, validity, interpretation, or scope, shall be resolved exclusively through binding arbitration in Geneva, Switzerland. The arbitration shall be conducted in English under the Rules of Arbitration of the International Chamber of Commerce (ICC) in effect at the time of the arbitration.

The arbitral tribunal shall consist of one arbitrator appointed in accordance with the ICC Rules. The arbitral award shall be final and binding, and judgment upon the award rendered by the arbitrator may be entered in any court having jurisdiction thereof.

This clause is intended to facilitate efficient resolution and international enforcement under the United Nations Convention on the Recognition and Enforcement of Foreign Arbitral Awards (New York Convention, 1958) , to which over 170 nations are party, ensuring that arbitral awards rendered under this Agreement are enforceable in virtually every jurisdiction worldwide.

8.3 Compliance with Local Laws

Notwithstanding the governing law and arbitration clause, You agree to comply with all applicable local laws and regulations regarding intellectual property and content use in Your jurisdiction(s). Where local law provides stronger protections for Licensor's rights than those provided in this Agreement, those stronger protections shall apply. Where local law limits or precludes certain provisions of this Agreement, such provisions shall be modified to the minimum extent necessary to comply with local law while preserving their intended effect.

8.4 International Treaty Recognition

This Agreement is intended to be interpreted consistently with and to benefit from the protections afforded by:

9. Disclaimers and Limitation of Liability

9.1 Disclaimer of Warranties

The Content is provided "AS IS" and "AS AVAILABLE," without warranty of any kind, either express or implied, including but not limited to warranties of merchantability, fitness for a particular purpose, accuracy, completeness, non-infringement, title, quiet enjoyment, or that the Content will meet Your requirements or be available on an uninterrupted, secure, or error-free basis.

9.2 Limitation of Liability

To the maximum extent permitted by applicable law, in no event shall Licensor be liable for any direct, indirect, incidental, special, consequential, exemplary, or punitive damages (including damages for loss of profits, goodwill, use, data, business interruption, or other intangible losses) arising out of or relating to Your access to or use of, or inability to access or use, the Content, regardless of the theory of liability (contract, tort, negligence, strict liability, or otherwise), even if Licensor has been advised of the possibility of such damages. Licensor's total cumulative liability under this Agreement shall not exceed one U.S. dollar ($1 USD).

9.3 Indemnification

You agree to indemnify, defend, and hold harmless Licensor from and against any and all claims, liabilities, damages, losses, costs, and expenses (including reasonable attorneys' fees and costs of investigation) arising out of or relating to (a) Your use or misuse of the Content, (b) Your violation of any term of this Agreement, (c) Your violation of any third-party right, including without limitation any intellectual property right, privacy right, or publicity right, or (d) any claim that Your use of the Content caused damage to a third party.

10. General Provisions

10.1 Severability

If any provision of this Agreement is held by a court or arbitrator of competent jurisdiction to be invalid, illegal, or unenforceable, such provision shall be modified to the minimum extent necessary to make it valid, legal, and enforceable, or severed if modification is not possible. The remaining provisions shall continue in full force and effect. The invalidity or unenforceability of any provision in any jurisdiction shall not affect the validity or enforceability of such provision in any other jurisdiction.

10.2 Entire Agreement — Supersession of Prior Licenses

This Agreement (the QNFO Unified License Agreement v2.0) constitutes the entire agreement between You and Licensor regarding the subject matter herein and supersedes all prior or contemporaneous understandings, agreements, representations, and warranties, both written and oral, including but not limited to:

All Content previously governed by any of the above licenses is hereby re-licensed under this Agreement. This re-licensing is effective as of the Effective Date of this Agreement and applies retroactively to all Content created prior to the Effective Date and prospectively to all Content created thereafter. Any person or entity that accessed, used, or relied upon Content under a prior license is hereby bound by this Agreement as of the Effective Date.

10.3 Changes to License

Licensor reserves the right to modify this Agreement. Changes will be effective upon posting the revised version to https://qnfo.org/legal/license or https://qwav.tech/legal/license. Your continued use of the Content after such changes constitutes Your acceptance of the revised Agreement. Material changes will be accompanied by a version number update (e.g., v2.0 → v2.1 or v3.0). The version of this Agreement applicable to any particular use of the Content is the version in effect at the time of such use.

10.4 Waiver

No waiver of any term of this Agreement shall be deemed a further or continuing waiver of such term or any other term. Licensor's failure to assert any right or provision under this Agreement shall not constitute a waiver of such right or provision. Licensor's decision not to enforce this Agreement against any particular person, entity, or use shall not constitute a waiver of Licensor's right to enforce this Agreement against any other person, entity, or use, nor shall it create any implied license, estoppel, or defense of laches, acquiescence, abandonment, or implied consent. Licensor's copyright in the Content is not abandoned, dedicated to the public domain, or otherwise waived by this Agreement, by Licensor's publication of the Content, by Licensor's failure to enforce any provision of this Agreement, or by Licensor's designation of any Content as Public Content under Section 1.5. Any waiver must be in writing and signed by Licensor to be effective. Delay in enforcement shall not be construed as waiver.

10.5 Machine-Readable Licensing — SPDX Identifier

The SPDX License Identifier for this Agreement is LicenseRef-QNFO-ULA-2.0. This identifier enables automated license compliance checking by software package managers, development tools, and platform services.

All source code files governed by this Agreement should include a machine-readable SPDX header as specified in Section 3.1. Software packages governed by this Agreement should include the following in their package manifest (package.json, Cargo.toml, pyproject.toml, etc.):

"license": "LicenseRef-QNFO-ULA-2.0"

10.6 License Compatibility

For purposes of the ShareAlike requirement (Section 4), the following licenses are considered compatible:

This list is not exhaustive and may be supplemented by Licensor. However, No license that permits commercial use is compatible with the ShareAlike requirement of this Agreement, as CC BY-NC-SA 4.0's NonCommercial restriction is a material term that must propagate to all derivative works.

10.7 Separate Commercial License — Public Benefit Framework

Licensor may, at Licensor's sole and absolute discretion, grant separate commercial use licenses on a case-by-case basis. Such licenses will be documented in a separate written agreement between Licensor and the licensee.

(a) Public Benefit Evaluation Criteria: In evaluating requests for commercial licenses, Licensor will consider, among other factors:

  1. Public Benefit: Whether the proposed commercial use demonstrably serves the public good — through scientific advancement, education, environmental sustainability, humanitarian causes, public health, cultural enrichment, or other socially beneficial outcomes.
  2. Accessibility: Whether the proposed use would make the Content or derivative works broadly accessible to the public (e.g., open access, free tiers, public interfaces) rather than exclusively paywalled or restricted.
  3. Contribution to the Commons: Whether the proposed use contributes back to the commons — through open-source code contributions, open data sharing, research publications, educational resources, or similar contributions that advance collective knowledge.
  4. Alignment with Values: Whether the proposed use is consistent with the values and principles expressed in the Preamble to this Agreement, including human dignity, ethical innovation, and anti-exploitation.
  5. Track Record: Whether the licensee has a demonstrated track record of ethical conduct, respect for intellectual property, and compliance with license terms.
  6. Scale and Impact: The scale of the proposed commercial use and its potential impact — both positive (public benefit) and negative (market enclosure, competitive harm to non-commercial uses).
  7. Jurisdiction: The legal jurisdiction(s) in which the proposed use would occur and the enforceability of license terms in those jurisdictions.

(b) Types of Commercial Licenses Available: At Licensor's discretion, commercial licenses may include:

  1. Perpetual Commercial License: A one-time grant of rights for a specific commercial use, with or without ongoing royalties.
  2. Revenue-Share License: A license where Licensor receives a percentage of revenue generated from the commercial use of the Content.
  3. Public-Benefit Conditional License: A license conditioned on the licensee meeting specific public benefit commitments (e.g., open-sourcing derivative works, contributing to public research, maintaining free access tiers).
  4. Time-Limited License: A license for a specific duration, after which rights revert to the non-commercial terms of this Agreement.
  5. Field-Limited License: A license restricted to a specific field of use, industry, or application.
  6. Territory-Limited License: A license restricted to specific geographic territories.
  7. Custom License: Any other license terms negotiated between Licensor and licensee.

(c) Application and Approval Process:

  1. Interested parties must contact Licensor in writing at the contact addresses provided in Section 11.
  2. The request should describe: the proposed commercial use, the specific Content to be used, the public benefit of the proposed use, the expected scale and duration of the use, and the proposed license type from subsection (b) above.
  3. Licensor will review the request and may request additional information.
  4. Licensor may approve, deny, or conditionally approve the request at Licensor's sole discretion.
  5. If approved, a separate written agreement will be executed between Licensor and licensee.

(d) Important Limitations:

The availability of separate commercial licensing does not:
- Obligate Licensor to grant any particular commercial license or to respond to any particular inquiry
- Constitute a waiver of any rights under this Agreement
- Create any legitimate expectation of receiving a commercial license
- Create any implied commercial license or estoppel claim
- Limit Licensor's ability to impose conditions, royalties, public benefit commitments, or other terms in any separate commercial agreement
- Preclude Licensor from charging different royalty rates or imposing different terms for different licensees

(e) Existing Commercial Relationships: Licensees who entered into commercial use agreements with Licensor prior to the Effective Date of this Agreement shall continue to be governed by the terms of those agreements until their expiration or termination, at which point any continued use of the Content shall be governed by this Agreement unless a new commercial agreement is executed.

(f) No Implied Commercial License: Nothing in this Agreement shall be construed as granting any implied commercial license, and no commercial use of the Content is permitted without a separate written agreement signed by Licensor. The absence of a response to a commercial license inquiry shall not be construed as approval, acquiescence, or waiver.

10.8 Survival

The provisions of Sections 3 (Attribution), 5 (Patent Prior Art Citation), 6 (Breach and Consequences), 7 (Intellectual Property Ownership), 8 (International Governance), 9 (Disclaimers and Limitation of Liability), and 10 (General Provisions) shall survive any termination of this Agreement.

11. Contact Information

For questions about this license, the Content, to report suspected violations, or to request a separate commercial use agreement (for entities wishing to use the Content commercially in alignment with the public benefit framework), please contact:

Rowan Brad Quni-Gudzinas (Licensor)

Appendix A — CC BY-NC-SA 4.0 Summary (For Reference)

The CC BY-NC-SA 4.0 license permits:

Under the following terms:

These terms apply in addition to the QNFO Supplemental Terms (Sections 2–10 above).

Appendix B — License Migration Notice

Effective May 29, 2026, the following prior licenses are terminated and superseded for all Content across the QNFO and QWAV ecosystems:

Prior License Previous Scope Superseded By
QNFO Content License Agreement v1.1 qnfo.org, QWAV, prompts QNFO-ULA v2.0
AI System License Agreement (ASLA) Root workspace, AI systems QNFO-ULA v2.0
CC BY-NC-SA 4.0 Obsidian vault, various projects QNFO-ULA v2.0
CC BY-NC 4.0 Various project-level files QNFO-ULA v2.0
MIT License git-on-cloudflare-deployment (third-party) QNFO-ULA v2.0 (for QNFO modifications only; upstream MIT components retain original MIT)
Unlicense (Public Domain) q08.org archive QNFO-ULA v2.0
Any project-specific or custom licenses Various projects QNFO-ULA v2.0

All references to prior licenses in existing project files, README documents, package manifests, and documentation shall be updated to reference this Agreement. This migration does not affect third-party dependencies (node_modules, vendor libraries, upstream components) governed by their own upstream licenses.

Migration Timeline

Phase Action Deadline
Phase 1 Replace root-level LICENSE files with pointers Immediate (Program Agent)
Phase 2 Update active project LICENSE files Within 7 days (Projects Agent)
Phase 3 Update archived project notices Within 30 days (Program Agent)
Phase 4 Update all code file SPDX headers Ongoing (Kaizen audit)
Phase 5 Deploy canonical text to qnfo.org/legal/license Immediate (Cloudflare Pages)

Appendix C — SPDX Header Templates

For Source Code Files

SPDX-License-Identifier: LicenseRef-QNFO-ULA-2.0
Copyright (c) [YEAR] Rowan Brad Quni-Gudzinas
Licensed under QNFO-ULA v2.0: https://qnfo.org/legal/license

For Documentation and Publications

# SPDX-License-Identifier: LicenseRef-QNFO-ULA-2.0
# Copyright (c) [YEAR] Rowan Brad Quni-Gudzinas
# Licensed under QNFO-ULA v2.0: https://qnfo.org/legal/license

For Package Manifests (package.json / Cargo.toml / pyproject.toml)

"license": "LicenseRef-QNFO-ULA-2.0"

Appendix D — Quick Reference Card

Question Answer
Can I use this for personal study? ✅ Yes
Can I use this in academic research? ✅ Yes (with attribution)
Can I use this for teaching? ✅ Yes (with attribution)
Can I use this in a non-profit project? ✅ Yes (with attribution, SA)
Can I sell this or use it commercially? ❌ No — not without separate agreement
Can a company use this internally? ❌ No — internal business use is commercial
Can I train my commercial AI on this? ❌ No — explicitly prohibited
Can I use this in an open-source project? ✅ Only if the project uses compatible NC-SA license
Can I get a commercial license? Maybe — contact Licensor (Section 11)
What if I violate the license? 85% liquidated damages + license termination
Does SA apply to my derivatives? ✅ Yes — derivatives must use compatible license
Is this international? ✅ Yes — Swiss law, ICC arbitration, 170+ nations
Can I scrape QNFO websites for data? ❌ No — automated scraping prohibited
Can I compile QNFO content into a dataset? ❌ No — dataset compilation prohibited
What about non-profit AI research? ✅ OK — with attribution + SA + non-commercial
Can a startup use this? ❌ No — startups are commercial entities
Can my university use this? ✅ Yes — educational use is permitted
Can I cite QNFO in my patent? ✅ Yes — and you MUST (see §5)

Appendix E — Frequently Asked Questions (Plain Language)

This FAQ provides plain-language guidance for common situations. The full license text (Sections 1–11) is the legally binding document. If there is any conflict between this FAQ and the license text, the license text controls.

For Developers

Q: I want to use QNFO code in my personal project. Can I?
A: Yes, as long as your project is non-commercial, you give proper attribution, and you license any derivatives under CC BY-NC-SA 4.0 (or this Agreement). If you're just learning, experimenting, or building something for yourself, you're fine.

Q: I want to use QNFO code at my company. Can I?
A: No. Using QNFO code for internal business operations, in a commercial product, or for any revenue-generating purpose is commercial use and requires a separate commercial license. Contact Licensor (Section 11) to discuss.

Q: What if my project is open source but I accept donations?
A: Accepting donations or sponsorships to support an open source project is not commercial use. But if you sell licenses, offer paid support tiers, or have proprietary add-ons that incorporate QNFO code, that's commercial use.

Q: Do I really need to include the SPDX header in every file?
A: Best practice, yes. For new projects, include it from the start. For existing projects, add it as you touch files. The Kaizen audit system will help track compliance.

Q: What license should I use for my derivative work?
A: CC BY-NC-SA 4.0 (or this Agreement). The ShareAlike requirement means your derivative must use a compatible non-commercial license.

For Researchers

Q: Can I cite QNFO work in my academic paper?
A: Yes — and please do! Just include proper attribution as specified in Section 3.1.

Q: Can I publish a paper that builds on QNFO theories in a paywalled journal?
A: If you're the AUTHOR of the paper, you can publish wherever you want — but the publisher cannot charge for access to QNFO Content itself without a commercial license. If you're the PUBLISHER (e.g., Elsevier, Springer Nature), you need a commercial license for paywalled publication incorporating substantial QNFO Content. Open access publication is always permitted.

Q: My research uses QNFO data to train a model. Do I need a license?
A: If the model is for academic research and the research results are shared openly (non-commercially), you're permitted under the standard license. If the model will be commercialized (even later), you should discuss a license with Licensor early.

Q: I'm filing a patent and my invention was influenced by QNFO work. What do I do?
A: You MUST cite QNFO (Rowan Brad Quni-Gudzinas, ORCID: 0009-0002-4317-5604) as prior art in your patent application. This is not optional — it's a material term of the license. Failure to do so can affect patent validity and constitutes a breach of this Agreement.

For AI/ML Practitioners

Q: Can I train my model on QNFO data?
A: It depends. If the model is for non-commercial research and the results are shared openly, yes. If the model is or will be commercial (including if your employer owns it, if you plan to offer it as a service, or if it's part of a commercial product), no — this is explicitly prohibited. Contact Licensor for a separate agreement.

Q: What about fine-tuning an existing commercial model with QNFO data?
A: Prohibited. Using QNFO Content to improve a commercial model is commercial use. Even if the fine-tuning is "experimental," if the improved model enters commercial service, it's a violation.

Q: Can I include QNFO Content in a public dataset like Hugging Face Datasets?
A: Yes, if the dataset is clearly licensed under CC BY-NC-SA 4.0 or this Agreement, and you provide proper attribution. The dataset must not be used for commercial purposes by downstream users. Include a prominent license notice.

Q: What if I discover someone using QNFO-trained models commercially?
A: Report it to Licensor (Section 11). Licensor will pursue enforcement under Section 6.6 (platform takedowns, legal action).

For Organizations

Q: Our non-profit wants to use QNFO Content. What do we need to do?
A: You can use it freely for your charitable/educational mission, with attribution and ShareAlike compliance. If you plan to commercialize any derivatives (including through a for-profit subsidiary), you need a separate license.

Q: Our company wants a commercial license. How do we apply?
A: Contact Licensor (Section 11) with: (1) description of proposed use, (2) specific Content to be used, (3) public benefit of the proposed use, (4) expected scale and duration, (5) preferred license type from §10.7(b). Licensor reviews requests case-by-case.

Q: We have an existing agreement with Licensor from before this license was created. Does this affect us?
A: No. Existing commercial agreements remain in effect until their expiration or termination (§10.7(e)). At that point, continued use requires a new agreement under the current framework.

Q: What happens if we violate the license?
A: The license terminates automatically. You must cease all use immediately. You may be liable for liquidated damages (85% of gross revenue from the violation). Licensor may pursue legal action and platform-level enforcement (takedowns, delisting).

General

Q: Does this license apply to everything QNFO/QWAV has ever created?
A: Yes. As of May 29, 2026, all QNFO and QWAV Content — past, present, and future — is governed by this Agreement (§1.3, §10.2). Prior licenses are superseded.

Q: Can the license change in the future?
A: Licensor may update the license (§10.3). New versions will be posted at https://qnfo.org/legal/license. Your continued use of the Content after a change means you accept the new version.

Q: I'm not a lawyer. How do I know if my use is OK?
A: Start with the Quick Reference Card (Appendix D) and this FAQ. If you're still unsure, the principle is: does your use extract value for private gain without public benefit? If so, it's probably prohibited. When in doubt, contact Licensor.

Q: How do I report a violation?
A: Email [email protected] with details of the suspected violation. Include URLs, screenshots, model cards, or any evidence you have. Licensor will investigate and pursue enforcement as appropriate.

QNFO — advancing scientific understanding for the collective benefit of all.
QNFO Unified License Agreement v2.0 — Effective May 29, 2026