Hey everyone, After 3+ years building AI automation systems, I realized something: the bottleneck isn't the model. It's context and resources. Better context = better agents. But here's the real problem: everything is segmented. Your agents are in Pydantic AI. Your workflows are in n8n. Your knowledge is scattered. Your execution is fragmented. So I built AgeniusDesk, a unified platform that manages ALL of it: agents, workflows, knowledge, resources. One command center. No silos. What is it? A unified management layer for AI platforms, agents, and workflow frameworks (n8n, Pydantic AI, Flowise, etc.): - Multi-instance n8n visibility + control from one dashboard - AI agents (Pydantic, Claude, OpenAI, local models) as first-class citizens - Real-time error detection + AI diagnostics (catches issues before they blow up) - Agent Lab: write and debug code with AI, deploy instantly - Encrypted secrets vault (never plaintext, never exposed) - Shared resource layer: context, guardrails, execution contracts - Full local/self-hosted control (no vendor lock-in) Built on Python + FastAPI + Vanilla JS. Docker compose ready. Why I'm posting this here: This community gets it. You're not asking for another no-code builder or magic button. You're building real systems, running agents in production, managing multiple deployments. AgeniusDesk is built for that. What I want from you: Drop a comment and tell me: - → Are you managing multiple n8n instances or agents right now? - → What's your biggest pain point? (visibility? errors? scale?) - → Would you test-drive this if it solved that problem? I'm open-sourcing the whole thing. No strings. Just want to build something the community actually needs.

Just scrapped companies that doesn't have a website in C.R. just a small list of 30 Exported in a csv ready to make some sales. The csv contains the company name and their contact info.