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DJ ViralOS is an original self-hosted software project designed for creators, DJs and small teams who want to manage the complete social-content workflow from one environment.
I designed the project architecture and built its technical core around Linux, with separate local development capabilities, content analysis, export workflows and GPU-assisted processing.
The platform is being developed to reduce repetitive work involved in preparing content for multiple social networks while keeping the workflow under the user's control.
Current technical scope
• Self-hosted Linux backend
• Local development and testing mode
• AI-assisted content analysis
• FFmpeg-based media export pipeline
• GPU worker and GPU diagnostics
• SQLite-based application data
• Content preparation workflows for TikTok, Instagram, Facebook, Twitch and YouTube Shorts
• Structured analysis, export and distribution architecture
• Controlled Pre-Beta access and testing workflow
Current status: Technical Alpha / Pre-Beta. DJ ViralOS is actively being developed and tested; unfinished features are not presented as production-ready.
Original project developed within the NEXACORE TECH DI LECA / DJShopItalia ecosystem.
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I built a workflow that turns a business website into a testable AI phone receptionist.
The system analyzes the website, extracts services, staff, opening hours, policies, and other relevant information, then creates an isolated voice-agent demo for that business. Instead of sending a generic recording, we can provide a real phone number that allows the business to test the agent through an actual call.
When the website or scheduling system supports an integration, the agent can check availability and book appointments during the call. Otherwise, it safely captures the caller’s details and preferred time for staff follow-up.
If a business decides to continue after the demo, the same foundation can be expanded into a production receptionist with databases, customer-specific business rules, calendar and CRM integrations, confirmations, call summaries, analytics, and administrative controls.
The extracted information can also reveal gaps in the business website. Its content and structure can then be improved so both visitors and the AI receptionist receive clearer, more reliable information.
The main lesson I share is that website extraction alone is not enough. Information must be normalized, validated, and restricted to the source material before it can be used safely in a live voice conversation.
The demonstration uses a fictional dental clinic and real recordings from my working voice-agent system. No patient data, real customer information, or invented testimonials are included.
I used Descript to assemble and refine the presentation, edit the narration and real-call sections, create captions, and prepare the final submission.
Most development relationships end at the first deliverable. The handover costs the client weeks and the next developer starts from zero.
Neurosync needed someone who stayed — through one product, then the next, holding the context that never makes it into documentation.
The part nobody prices is the undocumented context — why the discount stacks in that order, which one client the odd VAT rule exists for, the migration you deliberately left half-finished. I've stayed with a few clients across three and four builds, and by the third one the...