Scalytics Announces General Availability of LST-E: Advanced Energy Consumption Forecasting Model

Scalytics announces LST-E, an LSTM-based model for accurate energy forecasting, enabling optimized usage, cost savings, and compliance with data regulations.

MIAMI, FL, UNITED STATES, November 22, 2024 /EINPresswire.com/ -- Scalytics, a leader in decentralized data and AI solutions, is proud to announce the general availability of LST-E, a neural network for energy consumption forecasting. Built on Long Short-Term Memory (LSTM) architecture, LST-E provides businesses and energy organizations with precise and scalable predictions based on historical energy consumption data. This innovative model empowers organizations to optimize energy usage, reduce operational costs, and support sustainability goals by minimizing their carbon footprint.

"LST-E showcases the power of Scalytics in enabling businesses to solve real-world problems through precise, federated, and scalable AI solutions," said Alexander Alten, CEO of Scalytics. "Our federated platform ensures that domain-specific AI models like LST-E can deliver actionable insights while maintaining compliance and reducing data complexity."

Designed for large-scale datasets and real-time streams, LST-E handles complex, decentralized energy data environments, making it ideal for utilities and energy companies. By delivering accurate energy consumption predictions, the network enables users to make precise decisions in dynamic energy markets. Additionally, LST-E supports sustainability initiatives by optimizing energy use, reducing costs, and lowering emissions.

Unlike traditional models that require centralized data for training, LST-E leverages Scalytics Connect to train directly where the data resides. This federated approach ensures compliance with strict data regulations, minimizes infrastructure costs, and eliminates risky data movement. Organizations can also integrate their own domain-specific data, enabling LST-E to achieve higher accuracy, explainability, and trustworthiness compared to generalized models.

While LST-E is designed for energy forecasting, its flexible architecture supports applications across other domains, including water level forecasting, stock price prediction, and more. Scalytics’ focus on domain-specific, explainable AI enables businesses to address diverse challenges with tailored, high-performance solutions.

LST-E is available for download on GitHub and HuggingFace.

About Scalytics
Scalytics is a leader in federated data access and decentralized AI solutions. With its flagship platform, Scalytics Connect, the company empowers businesses to process data directly at its source, reducing costs, ensuring compliance, and unlocking the full potential of AI. Scalytics’ technology is transforming industries like energy, healthcare, finance, and retail by making secure, scalable, and regulation-compliant AI accessible to all.

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