Sigmafine is a model-driven software solution that validates and reconciles streaming data and events. Sigmafine simplifies and automates the process of generating usable datasets for people, business processes, and other applications and systems in the process industries.
Sigmafine combines process knowledge, engineering principles, and statistics to maximize the quantity, value, and quality of information extracted from disparate data sources and sensor-based data regardless of the industry or the use case.
Transforming Data into Digital Assets
Sigmafine provides a centralized framework and infrastructure to organize and automate data validation, reconciliation, and conditioning activities. Sigmafine can scale from very small to very large models and can be extended to support advanced and industry-specific analytics.
Introducing the SigmafineHub®
SigmafineHub evolves the user experience from an application centric experience to an integrated experience where all the features and functions are centrally managed (i.e. the Hub) and accessed through a series of web apps.
Join us May 16-19 at AVEVA PIWorld Amsterdam 2022 and stop by our booth in the exposition hall. Discover AVEVA’s vision and the exponential offerings of the AVEVA portfolio with their first in-person event as a combined company. This is your opportunity to learn from AVEVA + PI System experts, be inspired by fellow industry leaders, and hear about the latest innovation in digital transformation. AVEVA PI World has a lot to offer, and you won’t want to miss it.
Pimsoft announces the launch of a new product in the Sigmafine® family, SigmafineHub®. SigmafineHub is the result of two years of investment in developing a unique and innovative platform that can transform streaming data and events into Digital Assets. SigmafineHub is how Pimsoft accompanies customers in their digital transformation journey by providing a scalable, extensible, and adaptive framework for model-based data analysis.
Enterprise-wide software platform improves accuracy, usability of measurement data to reduce losses and mitigate financial risk