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What is Okyline?
Okyline is an Executable Data Design (EDD) platform that transforms validation contracts into executable operational assets for enterprise data quality.
Instead of multiplying specifications, custom validators, monitoring scripts, tests, and reporting layers, Okyline relies on a single readable contract shared across validation, quality control, and operational monitoring activities.
The contract itself becomes executable and directly drives deterministic validation, advanced business invariant verification, multi-format processing, data quality gates, operational metrics, and historical quality analytics.
Okyline validates APIs, enterprise events, files, streaming payloads, LLM structured outputs, and distributed data flows while continuously producing measurable quality indicators, completeness statistics, validation traces, and error propagation insights.
Because contracts are created from annotated sample data, validation rules remain immediately understandable for developers, architects, QA teams, integration specialists, and business analysts.
The Community Edition includes the public specification, a free Java validation runtime, a Claude AI assistant for contract generation, JSON Schema transpilation support, and a free online studio for executable JSON contracts.
The Enterprise Edition extends the same contract-centric model to native validation of JSON, JSONL, XML, CSV, FIXED, and EDI flows, combined with operational quality dashboards, data quality gates, and long-term quality tracking capabilities, all without requiring databases, warehouses, or centralized infrastructure.
What is APERIO DataWise?
Data is fundamental to all operations within a processing facility, acting as the cornerstone for workflows, strategic planning, and environmental oversight. However, complications often arise from this very data, leading to operator errors, faulty sensors, safety issues, or subpar analytics. APERIO is designed to effectively tackle these problems. The reliability of data is essential for Industry 4.0, supporting advanced applications such as predictive analytics, process optimization, and custom AI solutions. APERIO DataWise, known for its robust reliability, stands out as the leading source of trustworthy data. By automating the quality assurance for your PI data or digital twins in a scalable and continuous manner, organizations can guarantee validated information that enhances asset dependability. This not only enables operators to make well-informed decisions but also helps in identifying risks to operational data, which is crucial for sustaining operational resilience. Additionally, it offers accurate monitoring and reporting of sustainability metrics, thus fostering more responsible and efficient practices. In the current landscape driven by data, harnessing dependable information has transitioned from being a mere advantage to an essential requirement for achieving success. The integration of high-quality data solutions can transform the way organizations approach their operational challenges and sustainability goals.
Integrations Supported
Apache Kafka
PostgreSQL
AVEVA Connect
Amazon SageMaker
Azure Machine Learning
CitectHMI
Dagster
Daybreak
Grafana Cloud
Honeywell Forge
API Availability
Has API
API Availability
Pricing Information
Free Community Edition
Free Community Edition for executable JSON validation contracts. Enterprise Edition available for multi-format operational validation, dashboards and data quality gates.
Free Version
Pricing Information
Pricing not provided
Supported Platforms
SaaS
Windows
Mac
On-Prem
Linux
Supported Platforms
SaaS
On-Prem
Customer Service / Support
Web-Based Support
Customer Service / Support
Standard Support
Web-Based Support
Training Options
Documentation Hub
Training Options
Documentation Hub
Webinars
On-Site Training
Company Facts
Organization Name
Akwatype
Date Founded
2017
Company Location
France
Company Website
okyline.io
Company Facts
Organization Name
APERIO
Company Location
United States
Company Website
aperio.ai/aperio-datawise/
Categories and Features
Categories and Features
Data Quality
Not specified