GoPX.ai logo — blue atomic network mark GoPX.ai
Book a demo
Research foundation

Three decades of peer-reviewed work, six filed IP disclosures, one founder.

GoPX is the commercial expression of decades of research at ASU's CIPS-AI Lab. Every claim on the platform traces back to a published paper, a filed disclosure, or a deployed reference implementation. This page collects the public basis for the claims.

Selected research

Selected research

The intellectual foundations of GoPX.ai — peer-reviewed work on programmable AI, agentic workflows, and explainable reasoning.

  1. 2024 Programmable AI

    Toward a Programmable Humanizing Artificial Intelligence Through Scalable Stance-Directed Architecture

    Çetinkaya, Y.M., Lee, Y., Külah, E., Toroslu, I.H., Cowan, M.A., Davulcu, H.

    IEEE Internet Computing, Vol. 28(5), pp. 20–27 · Special Issue on Civilizing and Humanizing AI

  2. 2025 Explainable analytics

    NARRA-SCALE: Scaling Users and Messaging Through Narrative Detection in Retweet Networks

    Çetinkaya, Y.M., Trivedi, A., Yanamandala, V.D., Cowan, M.A., Toroslu, I.H., Davulcu, H.

    IEEE ICTAI 2025, pp. 187–194

  3. 2024 Applied LLMs

    Targeted marketing on social media: utilizing text analysis to create personalized landing pages

    Çetinkaya, Y.M., Külah, E., Toroslu, I.H., Davulcu, H.

    Social Network Analysis and Mining, Vol. 14(1), Article 77

  4. 2022 Persuasive AI

    Effective Messaging on Social Media: What Makes Online Content Go Viral?

    Mousavi, M., Davulcu, H., Ahmadi, M., Axelrod, R., Davis, R., Atran, S.

    The Web Conference (WWW 2022), pp. 2957–2966

  5. 2004 Logical foundations

    CTR-S: A Logic for Specifying Contracts in Semantic Web Services

    Davulcu, H., Kifer, M., Ramakrishnan, I.V.

    WWW 2004

  6. 1998 Agentic workflows

    Logic Based Modeling and Analysis of Workflows

    Davulcu, H., Kifer, M., Ramakrishnan, C.R., Ramakrishnan, I.V.

    ACM PODS 1998

Protected inventions

Six IP disclosures filed with ASU SkySong.

Twenty-plus method claims underpin the GoPX stack. Three are the backbone of the Interpretable Human + AI framework — the others extend it across verticals and operational regimes.

  1. M26-023P Foundational

    Programmable Interpretable AI

    Symbolic pattern lifting and lowering — the core invention behind verified decision architecture. Translates neural outputs into logic-patterned narratives a human or machine can audit, correct, and re-deploy.

  2. M26-021P Safety

    Value-Aligned Stance-Directed Architecture

    Programmable stance-directed AI built on the lifting mechanism. Basis of the peer-reviewed 85% reduction in hallucination and toxicity from unrestricted LLMs.

  3. M26-103P Compliance

    Ideological Diagnostics Pipeline

    Practical framework for quantifying bias in LLMs — actionable diagnostics for mitigation strategies, regulatory oversight, and the trust reporting that regulated teams already have to produce.

  4. M26-117P Agentic

    Programmable Constraint Lowering for Autonomous Agents

    Mechanism for binding agent actions to verified rule sets at execution time. Action surfaces inherit the explanation chain from the rule layer, producing defensible audit trails by construction.

  5. M26-128P Vertical

    Multi-vertical Knowledge Representation Trees

    KRT structure that generalizes across verticals — same engine produces editable rule layers for legal, commerce, and policy domains without per-vertical retraining.

  6. M26-141P Sovereignty

    Sovereign Audit Trail Architecture

    Method for keeping decision evidence on infrastructure controlled by the deploying enterprise while permitting model-agnostic execution. Decisions and their rationale never leave the perimeter; only the model query path crosses.

Disclosure IDs verifiable via ASU SkySong Innovations. Exclusive commercial license to GoPX in progress.

Portrait of Dr. Hasan Davulcu
Founder

Dr. Hasan Davulcu

Founder, GoPX.ai · Professor, School of Computing and Augmented Intelligence, Arizona State University

Dr. Hasan Davulcu is a professor at Arizona State University's School of Computing and Augmented Intelligence, where he directs the Cognitive Information Processing Systems (CIPS-AI) Lab.

Ph.D. Computer Science, Stony Brook University · M.S. Computer Science, Stony Brook University · B.S. Mathematics, Middle East Technical University (METU)

ASU Faculty Profile Google Scholar CIPS-AI Lab

Frequently asked questions

What is GoPX.ai?

GoPX.ai builds verified decision architecture for enterprise AI. It lifts contracts, policies, regulations, catalogs, and other enterprise documents into structured logic, then binds model outputs to verified rules and source evidence.

How is GoPX different from ChatGPT, LLaMA, or other LLMs?

GoPX does not try to make one model memorize your domain. It keeps domain logic outside the model in an inspectable rule layer, so teams can audit decisions, edit constraints, and switch models without rebuilding the business logic.

Which enterprise AI risks does GoPX address?

GoPX is designed for the risks regulated buyers ask about first: catastrophic forgetting, weak learning, prompt injection, execution exposure, information sovereignty, and LLM independence.

How does GoPX reduce inaccurate AI outputs?

GoPX constrains outputs to verified rules and indexed evidence. Every decision returns the clauses, policies, rules, and reasoning artifacts used to reach it, which makes failures easier to detect, correct, and prevent from recurring.

Who is behind GoPX.ai?

GoPX is founded by Dr. Hasan Davulcu, Professor at Arizona State University's School of Computing and Augmented Intelligence and director of the CIPS-AI Lab. He has over two decades of peer-reviewed research on programmable AI, agentic workflows, sociocultural modeling, and explainable reasoning — published at ACM, IEEE, and NSF/DoD-funded venues.

How do I learn more or get in touch?

The featured paper — 'Beyond the Black Box: Programmable AI and Explainable Text Analysis for Trustworthy Social Intelligence' — is the newest formal statement of the lifting/lowering approach and is forthcoming in IEEE Transactions on Computational Social Systems. For partnership and enterprise pilot inquiries, use the contact form below.

See it on your documents.

A 45-minute session. We run your contracts, policies, or regulations through GoPX live and return structured logic, a decision walkthrough, and an honest read on fit. No pitch deck.

  • Run on your documents, not a generic demo
  • Structured logic + decision walkthrough
  • Honest read on fit — no pitch deck