Blog

Insights, deep dives, and perspectives from the awaBerry team on security, automation, and the future of AI-native device management.

9 April 2026
Machine Learning on Any Device: How the Smart Automation Framework and Agentic API Work Together

Machine learning workloads have a structural problem: the data, the compute, and the person running the job are rarely in the same place. Harald Hagen explains how the Smart Automation Framework and Agentic API together solve this — creating an automated ML infrastructure that reaches any device, handles data where it lives, and runs training and evaluation unattended.

Harald Hagen Harald Hagen
8 April 2026
Using the Smart Automation Framework to Detect Web Server Security Threats

The Smart Automation Framework is not just a productivity tool — it is a powerful security monitoring engine. Naomi Brooks shows how to use it to build automated detection for bot requests, anomalous traffic patterns, and web server attack signatures, with zero manual log review required.

Naomi Brooks Naomi Brooks
7 April 2026
Web Scraping at Scale: Cool Things You Can Do With the Smart Automation Framework

The Smart Automation Framework makes web scraping accessible to anyone who can describe what they want in plain English. Rita walks through the most powerful and creative scraping use cases — from live price tracking and competitor monitoring to structured data harvesting from sites that actively resist it.

Rita Willow Rans Rita Willow Rans
3 April 2026
awaBerry Version 2: A New Dimension of Device Automation

Version 2 marks the transition from a remote access platform into a full AI-native automation platform. Harald Hagen walks through what changed, what is new, and why the combination of the Smart Automation Framework and the Agentic API represents something fundamentally different.

Harald Hagen Harald Hagen
18 March 2026
Device as a Service: Secure LLM Integration via the awaBerry Agentic MCP Server

The awaBerry Agentic MCP Server makes your registered devices available as tools to any MCP-compatible large language model — letting Claude and other LLMs securely read from your devices, analyse the data, and return structured results, within a precisely scoped zero-trust boundary.

Naomi Brooks Naomi Brooks

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