The "Self-Driving Car" for Your Producing Wells

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Ambyint advantage

Artificial Intelligence meets Artificial Lift

Ambyint complements traditional physics based analysis with modern artificial intelligence trained and tuned using the industry’s largest labeled data set from over 12 years of industry experience.

Modern Physics Based Analysis

Traditional physics based analysis has been the foundation of artificial lift optimization for decades.  Ambyint lets production engineers take advantage of familiar techniques in an easy to use interface as a natural extension of their daily workflows.

Integrated Global Network at No Additional Charge

The complete Ambyint solution includes optional deployments of intelligent, adaptive controllers for data acquisition. Using a satellite based communication network, Ambyint can collect data from any well, any where in the world.

Webinar: Field Automation for Data Collection and Control in O&G Beyond SCADA

On July 24th, Ambyint will host a live webinar event featuring our CTO, Ryan Benoit. Ryan will be covering a number of increasingly important topics within the Oil & Gas industry, such as how the Internet of Things (IoT) is irreversibly changing the way businesses think about field automation and data collection, the advantages and disadvantages of SCADA, and the current and future states of leading-edge IoT technologies.

Affordable and Flexible Pricing

Ambyint solutions are priced based on the number of wells being monitored and managed. We offer a low subscription price that includes network communications and data transfer, without making our clients sign long term contracts. Customers deploying Ambyint solutions realize immediate cost savings from reduced wellsite visits and efficient lift systems to improved production from existing wells and greater productivity of existing staff.

ambyint product solutions
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High Resolution Adaptive Controllers

Ambyint HRACs are optionally deployed smart devices that are safely deployed at well site to collect high resolution data while using locally embedded logic to dynamically adjust control parameters in response to changing conditions.

Production challenges