About Us

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At VeridicaSystems, our research unites computer science, formal logic, and governance to build systems founded on truth and trust. We design for verifiability, transparency, and teleological alignment – ensuring technology serves its intended purpose and human values. Our interdisciplinary experts focus on three core research programs that reflect our mission and values of truth, verifiability, sound governance, and purposeful alignment: 

Our Decidable Systems program advances the theory and practice of formally decidable computing systems. We develop domain-specific logic languages and models that guarantee algorithmic decidability – every question posed or rule evaluated in these systems can be resolved conclusively by computation. By tailoring formal logic to avoid undecidable constructs, we enable automated reasoning that is both sound and complete. This research draws on formal methods, type theory, and computational logic to create tools like FFLL (a Finite Formal Logic Language) and FAPL (Formal Automated Policy Language). These languages restrict logic to decidable fragments (similarly to OWL ontologies that use fragments of first-order logic for guaranteed decidability) so that consistency checks and inference can be fully automated. The result is machine-verifiable correctness: systems where policies, rules, and decisions can be exhaustively checked for logical consistency and necessary completeness. Our work in Decidable Systems lays the groundwork for software that is predictably reliable and mathematically provable, forming the backbone of truth-centric computing. 

This program focuses on making complex IT operations and organizational processes transparent, auditable, and trustworthy. We research techniques to embed verifiability into every action a system takes – from data generation and transformation to decision-making. Key topics include data provenance, secure audit trails, and formal governance policies. We leverage cryptography and distributed ledger technology (e.g. blockchain) as “norm-enforcing layers” to ensure integrity. For example, our researchers design cryptographically sealed log structures where each event or decision is linked to tamper-evident hashes and digital signatures. Once recorded and verified, such immutable records serve as anchoring truths for subsequent inferences. This approach yields a formal epistemic architecture that cannot be altered without contradiction, meaning the system’s truth claims can always be externally validated against an indelible history. Additionally, we investigate verifiable credentials and consent ledgers to enforce governance: participants and agents in a system carry cryptographic credentials, and their actions (such as data access or transactions) are checked against consent policies in real time. By combining these elements, the Verifiable Operations & Governance research ensures that organizations can trust their IT operations – every decision is explainable and every process is accountable. This work directly supports regulatory compliance, security auditing, and ethical AI, as well as fosters stakeholder confidence that systems are behaving in good faith. 

In our IT Operations research, we bridge advanced formal techniques with real-world enterprise IT systems and practices. The goal is to embed truth and alignment into day-to-day IT workflows and infrastructure. A major theme is teleological alignment – ensuring that automated operations and AI-driven processes continually serve the organization’s overarching goals and values. Our researchers examine how to integrate the outputs of the Decidable Systems and Verifiable Governance programs into practical tools for IT operators, DevOps pipelines, and decision-makers. For instance, we study streaming data lineage in cloud and DevOps environments: capturing data flows and transformations in real time to build an ongoing “chain of custody” for data. This helps operators trace any output back to its inputs, configurations, and responsible agents, which is crucial for diagnosing issues and proving compliance. We also develop explainable analytics for IT operations – from root-cause analysis systems that automatically explain incidents to explainable AI models that justify their resource allocation or alerting decisions. (For example, applying our truth-maintenance approach to AIOps, an anomaly detection system would not only flag an outlier but also provide the logical and evidence-based rationale behind it, akin to providing reasons behind an AI-driven credit score.) Moreover, this research area covers policy-driven automation, where IT management actions (deployments, access controls, incident responses) are governed by formal policies written in our decidable languages. By validating each automated operation against these formal policies, we ensure governance compliance even in continuous deployment environments. Overall, the IT Operations research program turns abstract principles into operational reality – creating IT systems that are self-auditing, aligned with business objectives, and resiliently truth-centric in their behavior. 

Across all our research programs, VeridicaSystems emphasizes cross-disciplinary collaboration. Our work sits at the intersection of computer science, information security, AI, and organizational science. By uniting these fields, we aim to build systems people can trust – systems that are not only technically robust but also aligned with human and societal needs.