[D] Exploring Local-First AI Workflow Automation

[D] Exploring Local-First AI Workflow Automation

Hi all,

I’ve been experimenting with an open-source approach to AI workflow automation that runs entirely locally (no cloud dependencies), while still supporting real-time data sources and integrations. The goal is to provide a privacy-first, resource-efficient alternative to traditional cloud-heavy workflow tools like Zapier or n8n, but with LLM support integrated.

👉 My question for the community:
How do you see local-first AI workflows impacting ML/AI research, enterprise adoption, and robotics/IoT systems where privacy, compliance, and cost efficiency are critical?

• Repo: Agentic Signal (open-source, AGPL v3 / commercial dual license)
• Demo video: YouTube link

Would love feedback from both the research and applied ML communities on potential use cases, limitations, or challenges you foresee with this approach.

Thanks!