5.0 out of 5 stars
(2 Ratings)
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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4.9 out of 5 stars
(8 Ratings)
For developers, ARGOS Identity offers two APIs.
ARGOS ID Check (KYC/eKYC): launch the hosted Liveform from one URL in a browser or an iOS, Android or React Native WebView, or build your own capture UI on the Verify engine APIs. Your backend uses the REST API to fetch submissions, review pending cases, delete or partially delete data for GDPR and CCPA requests and download AML reports, and receives webhooks for created, submit, approved, rejected, updated, delete and AML result events. Each check reads the ID with OCR plus MRZ and PDF417 barcode checks, tests ID and selfie liveness, matches the face to the ID photo and screens the user against sanctions and PEP lists, with ongoing monitoring afterwards. Data is processed and stored in the region chosen for each project (US or South Korea), sensitive fields are encrypted with AES-256 at rest, and payload encryption is optional. A migration API imports existing verification records.
ARGOS Omni (Review Ops Agent): authenticate with an x-api-key header, create a profile under a workflow, upload files, text or JSON as items (PDF, DOCX, XLSX, PPTX, images, CSV, HTML, EML and more) and start an asynchronous analysis. The result follows the output schema you defined, with a verdict of verified, rejected or pending_review and the reasoning and source step for each extracted value, and every completed analysis can be downloaded as a PDF report.
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Liquid XML Data Binder
Liquid XML Data Binder allows you to load XML Documents in a strongly-typed object model from your C#, C++ Java, Visual Basic.Net, or VB6 source code. This means fewer coding mistakes, reduced development and test time, and increased schema conformance and code reliability.
Liquid XML Data Binder Features:
- Generates a class library that is easy to use for C++, C# Java, Visual Basic.Net and VB 6(COM) from an XML schema.
- Generated HTML documentation of your class library API.
- Supports Smart Device Platforms Android and iOS.
- Supports W3C XML Schema, XDR, and DTD standards.
- Supports generating WCF Web Services using WSDL.
Supports JSON serialization.
- Supports Fast Infoset binary XML Serialization.
- Support the most complex XML standard.
- Distribution of compiled code, runtime and other software without any additional fees.
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Open mHealth
Data schemas define the structure and content of various types of information, such as blood glucose levels, influencing how software applications manage that information. Often, systems must accommodate data from multiple devices or platforms, each presenting information in its own unique way. When all data related to a specific metric, like blood glucose, adheres to a unified schema, it becomes significantly easier to analyze and interpret that information, regardless of its original source. A standardized schema acts as a consistent point of reference for documentation, facilitating the use of data points across different contexts. In the realm of healthcare, the importance of common data schemas is magnified due to the intricate nature and significance of health-related information. For instance, recognizing the difference between fasting and non-fasting blood glucose levels is crucial for accurate clinical interpretation and decision-making. This shared understanding ensures that healthcare professionals can communicate effectively and make informed decisions based on reliable data.
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