
Okyline is an Executable Data Design (EDD) platform focused on executable validation contracts and operational data quality control.
Rather than managing separate specifications, validation code, tests, and monitoring dashboards, Okyline centralizes validation and quality supervision around a single readable executable contract acting as the operational reference for enterprise data flows.
The same contract powers deterministic validation, advanced business invariant checks, multi-format execution, data quality gates, and historical quality analytics across APIs, events, files, LLM structured outputs, and distributed operational systems.
Contracts are designed directly from annotated sample data, making validation rules immediately understandable for developers, architects, QA teams, and business analysts.
The Community Edition includes the public specification, a free Java runtime engine, a Claude AI assistant for contract generation, and an online studio supporting executable JSON validation contracts and JSON Schema transpilation.
The Enterprise Edition adds native validation for JSONL, XML, CSV, FIXED, and EDI flows together with operational quality dashboards and data quality gates, without requiring databases or centralized infrastructure.erprise Edition supports direct validation of JSON, JSONL, XML, CSV, FIXED, and EDI flows with operational quality dashboards and analytics, without databases.
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Airlock Digital delivers an easy-to-manage and scalable application control solution to protect endpoints with confidence. Built by cybersecurity professionals and trusted by organizations worldwide, Airlock Digital enforces a Deny by Default security posture to block all untrusted code, including unknown applications, unwanted scripts, malware, and ransomware.
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SAS Business Rules Manager
Minimize the likelihood of piecemeal and reactive operational decision-making by implementing analytically based business rules to enhance and streamline decisions throughout your organization. The SAS Business Rules Manager offers a centralized repository for rules, serving as a unified platform for overseeing the development and implementation of rules, along with automating workflows. Administrators benefit from a singular control point that manages user authorization, access, and security settings for each individual. An integrated workflow allows for the customization of processes while ensuring that all publishing activities are traceable and properly versioned. Furthermore, the system grants detailed control over rule functionalities, which upholds role-based security to confirm that users possess the necessary authorizations. By leveraging analytical modeling, businesses can extract rules directly from their operational data, enabling the automatic production of rule definitions and associated vocabularies. This approach not only enhances decision-making but also fosters a more consistent and reliable operational environment.
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Plurai
Plurai serves as a real-world trust platform dedicated to AI agents, designed for simulation-based assessment, safeguarding, and enhancement, effectively transforming agents into dependable and progressively advanced production systems. It assists teams in developing evaluations and protective measures specific to their requirements, facilitating the transition from initial prototypes to robust, scalable production. Plurai's simulation framework equips agents for real-world challenges rather than controlled environments, employing hyper-realistic, product-specific experimentation and assessment that addresses the intricacies of production. The platform creates genuine multi-turn interactions, diverse personas, essential artifacts, and tool simulations, utilizing organizational PRDs, pertinent references, and policies to construct a knowledge graph that broadens edge-case coverage. By moving away from static datasets, manual test formulation, and inconsistent LLM evaluation methods, Plurai organizes assessments into coherent, executable experiments, enabling teams to test new iterations, track regressions, and confirm enhancements prior to deployment. Ultimately, this innovative approach ensures that AI agents are not only trusted but also continuously refined for optimal performance in dynamic environments.
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