Simplify Your AI Journey: The Scalytics Blog

Get practical solutions, federated learning strategies, and insights to accelerate your AI projects.

Why Agentic RAG Is the Next Big Thing in AI

Agentic RAG systems, built on the Agent Context Protocol (ACP), enable secure and collaborative AI workloads. ACP expands upon the Model Context Protocol (MCP) by adding a data firewall with governance, access control, and auditability layers. This allows decentralized agent communication, broad access to tools and data, and reliable operation within containerized environments.

Decentralizing AI to Scale Smarter With Federated Learning

Federated Learning (FL) addresses AI scalability challenges by enabling decentralized training on diverse data sources while maintaining privacy. Scalytics Connect v1.2.0 simplifies FL implementation with auditable and traceable workflows, supporting various platforms and data sources. This approach revolutionizes industries by democratizing AI benefits and ensuring data security and compliance.

LST-E: Our Industry-Specific Energy Forecasting Model

LST-E is Scalytics' advanced energy forecasting model built on LSTM architecture, designed to optimize energy usage, reduce costs, and lower emissions. Trained using federated learning on decentralized data, it ensures compliance while delivering highly accurate, actionable predictions. Available on GitHub and HuggingFace, LST-E empowers businesses to make smarter energy decisions with tailored, regulation-compliant AI solutions.

AI That Works for You: Scalytics Partner Program

The Scalytics Partner Program empowers ISVs and MSPs to deliver secure, scalable AI solutions with decentralized data processing. Overcome data silos, reduce cloud costs, and ensure compliance with GDPR and HIPAA while enabling enterprise AI adoption. Be an early mover in AI enablement and unlock new revenue opportunities with Scalytics Connect, the industry’s leading federated learning platform.

Shift-Left Architecture: A Decentralized Approach to Data Management (Part 2)

In our previous blog post, "The AI Problem: Data Silos and the Mantra of Centralization," we explored the persistent challenges organizations face with traditional data management approaches, particularly the issues of data silos and the inefficiencies of centralized systems. Building on that foundation, this post delves into the "Shift-Left Architecture," a contemporary approach to data management that emphasizes bringing algorithms directly to the data rather than moving the data itself.

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