
AnalyticsCreator is a metadata-driven design application for data warehouse automation and data product engineering across the Microsoft data stack.
Its Governed Control Model connects business meaning, data structures, transformation rules, dependencies, lineage and technical implementation in one controlled project model. Data teams design the required architecture in AnalyticsCreator, then generate native Microsoft assets from that design.
Generated outputs can include SQL Server objects, SSIS packages, Azure Data Factory pipelines, supported Microsoft Fabric components, deployment artefacts and Power BI semantic models. AnalyticsCreator supports dimensional, 3NF and hybrid modelling approaches together with ingestion, transformations, delta loading, historisation, Slowly Changing Dimensions, snapshots and repeatable data-processing patterns.
Because generated outputs are native Microsoft technology, no AnalyticsCreator runtime is required in production. Organisations retain ownership of the resulting implementation and can integrate generated assets into Git, Azure DevOps and CI/CD workflows.
Lineage, documentation and dependency information remain connected to the design, helping teams understand change impact before regenerating affected assets.
Design Intelligence extends this governed project context into AI-assisted data engineering by providing authorised AI tools and agents with structured access to metadata, lineage, dependencies and design rules.
Typical use cases include enterprise data warehouse development, Microsoft Fabric adoption, SQL Server and SSIS modernisation, governed Power BI delivery and repeatable data product engineering.
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ARGOS Identity provides AI-powered identity verification, fraud prevention, KYB, and workflow automation solutions for businesses operating in regulated and high-risk industries.
ARGOS ID Check enables organizations to verify customers remotely using identity document authentication, facial recognition, selfie verification, liveness detection, AML screening, age verification, and additional fraud signals. The platform supports identity documents from more than 200 countries and is designed for fintech, gaming, virtual assets, e-commerce, telecommunications, and other digital platforms.
Businesses can configure their verification process by selecting the modules that match their compliance requirements and risk tolerance. ARGOS can help identify forged documents, deepfakes, duplicate users, bots, VPNs, and suspicious activity while maintaining a fast and straightforward onboarding experience.
For business verification, ARGOS Omni automates KYB and compliance workflows. Omni supports document collection and extraction, business registry searches, ownership and UBO identification, AML screening, case management, and audit reporting. Custom workflows and decision rules help teams reduce manual reviews and apply compliance policies consistently.
ARGOS gives businesses one flexible platform for verifying people and companies, preventing fraud, lowering operational costs, and scaling compliant onboarding.
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Sokratech
Sokratech is an advanced real-time fraud detection system tailored for banks and financial organizations. It efficiently evaluates transactions and provides a decision in less than 250 milliseconds by leveraging a no-code rules engine, machine learning risk assessments, and customizable workflows, enabling fraud teams to react to emerging threats in a matter of minutes instead of going through lengthy release cycles. Its features encompass continuous transaction oversight, governance over rules and models with comprehensive audit trails, transparent decision-making suitable for regulatory and audit scrutiny, and effective case management for fraud investigations. Specifically designed to meet the compliance and data residency requirements of regulated financial entities, Sokratech ensures that institutions can maintain high standards of security and accountability. The platform is delivered through API and seamlessly integrates with core banking and payment systems, allowing organizations to quickly implement it without the need to overhaul their existing infrastructure and processes, thus enhancing their operational efficiency.
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WizWhy
WizWhy analyzes how the values of one data field are influenced by the values of other fields in the dataset. The analysis hinges on a dependent variable chosen by the user, while the remaining fields act as independent variables or conditions. This dependent variable can be examined in two ways: as a Boolean value or as a continuous measurement.
Users have the ability to refine their analysis by setting various parameters, including the minimum probability for rule formation, the least number of instances required for each rule, and the comparative costs associated with false negatives versus false positives.
WizWhy identifies and presents a series of rules that connect the dependent variable with other fields, expressing these rules using if-then and if-and-only-if constructs. Based on the identified rules, WizWhy highlights significant patterns, reveals unexpected rules that may indicate interesting phenomena, and points out unusual cases within the dataset. Additionally, WizWhy is capable of making predictions for new instances by leveraging the established rules.
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