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What is Initial State?

Start your streaming adventure by utilizing simple URL parameters, or immerse yourself in the Streaming API documentation to learn how to send events in JSON format. Accessing data from your Initial State account is just as easy; you only need your private access key along with a straightforward HTTPS GET request. Discover our intuitive examples and extensive API documentation to guide you through the process. With no limits on the number of devices, data streams, or dashboards, you have the freedom to innovate and create impressive data projects. Whether you prefer to keep your information confidential or wish to share it with a larger audience, the Initial State streaming REST API simplifies both learning and implementation. A variety of open-source SDKs, including those for Python and NodeJS, are available for your ease. Moreover, you can explore several in-depth tutorials crafted to assist you in effortlessly developing functional real-time streaming projects. Our codeless data integrations further enhance this experience by allowing you to gather data from APIs with just a few clicks, removing the necessity for coding or setting up hardware to retrieve the information you seek. This efficient strategy not only makes it accessible but also enables you to concentrate on your creative projects without the hassle of complex technical details. Ultimately, the user-friendly nature of these tools encourages experimentation and innovation in data handling.

What is Crosser?

Harness the power of Edge computing to transform large datasets into actionable insights that are easy to manage. Collect sensor data from all your machinery and create connections to various devices such as sensors, PLCs, DCS, MES, or historians. Adopt condition monitoring for assets situated in remote locations, effectively adhering to Industry 4.0 standards to ensure optimal data collection and integration. Combine real-time streaming data with enterprise-level information for smooth data transitions, utilizing either your preferred Cloud Provider or an in-house data center for storage needs. Take advantage of Crosser Edge's MLOps features to implement, manage, and deploy your tailored machine learning models, while the Crosser Edge Node accommodates any machine learning framework. You can access a centralized repository for your trained models hosted in Crosser Cloud, and simplify your data pipeline with an intuitive drag-and-drop interface. Easily deploy your machine learning models across multiple Edge Nodes in a single action, enabling self-service innovation through Crosser Flow Studio. Benefit from an extensive collection of pre-existing modules that enhance collaboration among teams in different locations, significantly decreasing dependency on specific team members and boosting overall organizational productivity. By leveraging these advanced capabilities, your operational workflow will not only enhance collaboration but also drive innovation to unprecedented levels, paving the way for future advancements.

Media

Media

Integrations Supported

PubNub

Integrations Supported

Advantech WebAccess/CNC
Azure Stream Analytics
Barracuda PST Enterprise
Google Cloud Platform
Microsoft Azure
SIGNL4

API Availability

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided
Free Trial Offered?

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Not specified

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Online Training

Company Facts

Organization Name

Initial State

Date Founded

2012

Company Location

United States

Company Website

www.initialstate.com/streaming/

Company Facts

Organization Name

Crosser Technologies

Date Founded

2016

Company Location

Sweden

Company Website

www.crosser.io

Categories and Features

IoT Analytics

Not specified

Categories and Features

Condition Monitoring

Not specified

IoT

Not specified

IoT Analytics

Not specified

IoT Development

Not specified

Machine Monitoring

Not specified

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