In the coders channel, a founder of a top VoiceAI white label agency platform discussed the challenges of dockerizing their platform for local deployment.
They noted progress in reducing their system down to two containers and are now working toward a single container solution for easier mass deployment. A full stack and AI developer offered advice, highlighting that the hardest parts of local deployment are typically handling real-time voice dependencies, GPU access, networking, persistent storage, and maintaining low latency across different environments. They recommended separating services such as inference, API, database, and queue or worker, then containerizing them gradually rather than all at once. The same developer also introduced themselves to the community, sharing interest in AI integrations, workflow automation, SaaS platforms, backend systems, AI agents, dashboards, and productivity tools, and expressed openness to connecting with founders and developers on long-term projects.
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