AI Content Automation System

@shayankhan333

The trickiest part of this setup isn't the n8n workflows themselves, it's handling Meta Graph API token expiration and upload retries gracefully. Most automations break silently when a long-lived token expires or Meta rate-limits a batch upload. I'll build the n8n workflows inside Docker with FFmpeg processing, wire up Telegram Bot API for real-time job status alerts, and set up error recovery with automatic retry logic for Meta failures. One thing worth noting: n8n's built-in error workflow trigger is limited, so I'll use a custom error-catcher node pattern that logs failures to PostgreSQL before pushing to Telegram. 1) Are your n8n and Docker already running on the VPS, or is that part of the setup scope? Happy to talk details in chat. Shayan

@jaimikpanchal

Hello Sir/Madam, Greetings for the day! I am an experienced Automation Specialist with strong expertise in n8n workflow automation, API integrations, and business process optimization. I help businesses automate repetitive tasks, connect different platforms, and build efficient workflows that save time and improve productivity. Key Expertise: ✅ n8n Workflow Design & Development ✅ API Integrations (REST, Webhooks, OAuth) ✅ Business Process Automation ✅ Integration with tools like Google Sheets, Airtable, Slack, Telegram, Notion, Shopify, and Stripe ✅ Data synchronization and automated notifications ✅ Custom logic using JavaScript within n8n workflows Recent Automation Projects: ✔️ Lead capture automation from forms to CRM with notifications ✔️ E-commerce order automation with invoicing and email alerts ✔️ AI integrations using APIs for automated responses ✔️ Data syncing between multiple apps and databases ✔️ Automated alerts via Slack, Telegram, and email I specialize in creating reliable, scalable automation solutions using n8n, helping businesses streamline operations and reduce manual work. I would be happy to discuss how I can help automate and optimize your workflow. Best Regards

@gauravbhishm

A production automation system is only as good as its monitoring — silent failures cost more than the automation saves, so visibility into every job status matters as much as the pipeline itself. For this, I'd build a modular n8n workflow architecture running in Docker on your Linux VPS, wiring together the Meta Graph API, FLUX, and OpenAI GPT calls with FFmpeg for processing, and a dedicated monitoring layer that tracks successful/failed jobs, processing status, and error logs — pushed to you in real time via Telegram Bot API. PostgreSQL for job/state persistence if the volume needs it, with a backup workflow and clean env-variable config so it's easy to extend to YouTube Shorts, TikTok, or Pinterest later without rearchitecting. I've built backend systems with REST API integrations, cloud/VPS deployment, and structured error handling — the same principles apply directly here: clean architecture, documented, and built to scale. Estimated timeline: 5-6 days for the full build, tested end-to-end. Fixed price: ₹9,500. Quick question: is Meta upload failure the main pain point right now, or is monitoring needed across the full pipeline from day one?

@UmairBuildsAI

Hey, I can help build a scalable, production-ready AI content automation system using n8n, Docker, OpenAI, FLUX API, FFmpeg, Telegram Bot API, and the Meta Graph API with a clean, modular architecture that's easy to extend. You can review my work here: https://www.freelancer.pk/u/UmairBuildsAI AI automation and workflow orchestration are my core expertise. I'll develop robust n8n workflows to generate content, process media with FFmpeg, publish to Meta, handle upload failures with automatic retries, and provide real-time Telegram notifications for successful jobs, failed jobs, processing status, and detailed error logs. The solution will include Docker deployment, environment configuration, backup workflows, documentation, and a production-ready architecture that can later expand to platforms like YouTube Shorts, TikTok, and Pinterest. My focus is on reliability, maintainability, and seamless API integrations so the entire pipeline runs with minimal manual intervention. One quick question: do you already have the OpenAI, FLUX, and Meta APIs configured, or would you like me to handle the complete setup and deployment on your Linux VPS as well? Happy to jump on a quick call to review the project flow and get your project live smoothly. Best Regards, Umair

@FizzaMushtaq07

I am a full stack developer with more than 2 years of experience building n8n automations, Docker based deployments, REST API integrations, AI workflows, and scalable backend systems. Without resilient monitoring and recovery, failed uploads and long running jobs become difficult to diagnose and can interrupt the entire automation pipeline. I would build modular n8n workflows with centralized logging, Telegram notifications, retry mechanisms, FFmpeg processing, Meta Graph API integration, and Docker based deployment for reliable operations. I recommend separating processing, monitoring, and notification workflows because independent services are easier to scale and recover without affecting active jobs. Will jobs be triggered only from n8n webhooks, or should the system also support scheduled batch processing and queue based execution for future platforms like YouTube Shorts and TikTok? Happy to discuss details in chat. Regards, Fizza Mushtaq

@EthanKCK

ONE SMALL DETAIL IN YOUR PROJECT, COULD HAVE A BIG IMPACT ON THE FINAL OUTCOME. Monitoring upload failures is crucial for your AI Content Automation System, and a lack of comprehensive error logging can lead to unnoticed issues, impacting your scalability goals. In a similar project, I developed a robust n8n workflow for a social media automation tool that reduced error rates by 30% through proactive monitoring and error recovery setups. I fully understand your objective of creating a scalable, production-ready system. I will design a clean, modular architecture that not only meets your current requirements but also allows for future expansions, such as integration with YouTube Shorts and TikTok. My approach includes detailed documentation and a reliable backup workflow to ensure seamless operation. The difference between an average result and an exceptional one is usually decided before the work even begins. Regards, EthanKCK

@iproa2

I have experience building automation systems, REST API integrations, and full-stack web applications. I can develop a scalable, production-ready n8n automation that integrates OpenAI GPT API, FLUX API, Meta Graph API, Telegram Bot API, FFmpeg, Docker, and Linux VPS. The solution will include modular workflows, monitoring, error handling, retry logic, logging, Telegram notifications, backup workflows, and complete documentation for deployment and maintenance. The architecture will be designed to support future expansion to YouTube Shorts, TikTok, Pinterest, and other platforms. I provide clean, maintainable code, clear communication, and post-delivery support. I can start immediately and would be happy to discuss your requirements in detail. Estimated Timeline: 3–4Days Fixed Price: ₹1300 Looking forward to working with you.

@ZohaibSathio

I build exactly this: production n8n pipelines fusing image/text generation, FFmpeg rendering and social publishing with full failure monitoring. Relevant: shorts-factory (automated FFmpeg ingest->render->auto-publish, retry+error logs), Hermes (24/7 n8n automation agent on a Dockerised Linux VPS, webhooks/retries/audit), a FLUX/OpenAI generation pipeline, Telegram status bots. Plan: n8n -> FLUX+OpenAI -> FFmpeg -> Meta Graph API; Telegram bot reports success/failed/processing + error logs; PostgreSQL job state; retry/backoff + backup workflow; Dockerised with env vars + install docs; modular so Shorts/TikTok/Pinterest slot in later. ~7 days for a production v1, fixed price as bid. Is each post auto-generated from a topic, or do you supply a script/source per post?

@rakhshanz3

Hi! I build automation pipelines with n8n on Docker and can deliver this content-automation + monitoring system. I'll set up fully working n8n workflows that handle Meta Graph API uploads (including retrying/handling upload failures), with FFmpeg for media processing and OpenAI GPT for content. On top I'll build the monitoring layer that reports successful jobs, failed jobs, processing status and error logs, and pushes updates to you via a Telegram bot. Delivered on a Linux VPS with clean Docker configuration, documented environment variables, PostgreSQL if needed, and a modular architecture you can extend. I'll share n8n workflows I've built before. Quick question: roughly how many uploads/day should the pipeline handle, and is the VPS already provisioned or shall I set it up?

@philipj65

Hey bro!!! I totally get your requirements. No worries at all, man. They’re super easy for me and not a problem whatsoever. We can jump right in and get started immediately. But I got a quick question for you. Hit me up so we can talk more and sort everything out in detail.

@TimiTaiwo

I specialize in building production-ready n8n automation systems with AI integrations, Docker deployments, REST APIs, and robust error handling. I can develop a modular workflow that integrates OpenAI, FLUX, the Meta Graph API, FFmpeg, Telegram Bot API, and PostgreSQL (if required), with automated monitoring for successful jobs, failed jobs, processing status, and detailed error logs delivered directly to Telegram. My focus is on creating reliable, scalable automations that are easy to maintain and extend. I'll deliver clean, documented n8n workflows, Docker configuration, environment setup, installation guides, backup and recovery workflows, and a modular architecture designed for future expansion to platforms like YouTube Shorts, TikTok, and Pinterest. Based on the scope, I estimate 1–2 weeks for a fully tested production-ready implementation, and I'm happy to discuss a fixed-price proposal after reviewing your detailed requirements.

@carlosporter

Hello, I build production monitoring and automation systems that run reliably on Linux infrastructure, and this project matches the kind of work I do every day. I'm a Senior Site Reliability Engineer with 16 years in Linux/Unix systems and eight years supporting Azure customers. I've deployed and operated Docker containers, automated server operations with Ansible and Bash, and built self-hosted AI tooling stacks using Ollama, Open WebUI, and LiteLLM. I've also worked with REST APIs and PostgreSQL in incident-response setups, and I've set up notification workflows using custom scripts and APIs. While I haven't used n8n directly, I've built equivalent automation pipelines with custom scripts and orchestration tools, so I can ramp quickly on n8n's workflow model. My approach will be to assess the existing upload pipeline, design the monitoring workflows in n8n with Docker, implement FFmpeg integration and Telegram alerts, validate against Meta and FLUX APIs, and document everything including error recovery and backup workflows. I'll keep the architecture modular so future YouTube or TikTok expansions slot in cleanly. I can review your current setup and map out the first workflows. Carlos Porter Senior Site Reliability Engineer

@fronterasjohnval

Hello, I build practical n8n automations using APIs, webhooks, AI models, structured data, validation, logging, and documented recovery steps. My portfolio includes 18 automation workflows using OpenAI/Gemini and Google Workspace integrations, plus an AI-video workflow using FFmpeg. Because the posted ₹1,500 maximum budget is not realistic for the entire production system, my fixed bid covers Phase 1: • Receive and classify Meta upload results and failures • Record job status and error details • Send success/failure alerts through Telegram Bot API • Add retry and failure-routing logic in n8n • Provide the workflow export, environment-variable template, and setup documentation I can structure Phase 1 modularly so Docker, PostgreSQL, FLUX/OpenAI generation, backup workflows, and additional social platforms can be added as later milestones. Estimated timeline: 4 days. Fixed Phase 1 price: ₹1,500. Before starting, I would review your current workflow, sample Meta error payloads, n8n version, and VPS environment.

@pankajbehare

Experienced AIML and MLOPS engineer, I am aws and microsoft azure certified engineer work on various client and infrastructure and also resolved very complex production issue and launch production infra in timely manner. i am work various it tools like linux windows git cicd terraform cloudflare ansible prometheus grafana docker k8s terraform trivy sonarqube argocd owasp observability open-telemetry and so on and still working on learning on cloud ai certification.

@iamhasnainraja

Hi, I reviewed your AI Content Automation requirements and I'm interested in building a scalable, production-ready automation system using n8n, Docker, Linux VPS, OpenAI APIs, Telegram Bot API, FFmpeg, and PostgreSQL. I can build modular n8n workflows with proper error handling, retry mechanisms, monitoring, Telegram notifications, logging, and backup workflows. The solution will be containerized with Docker, well documented, and designed for future expansion to platforms like YouTube Shorts, TikTok, and Pinterest. My focus is on clean architecture, reusable workflows, secure environment variable management, and reliable automation that is easy to maintain and scale. Estimated Timeline: 7–10 Days I would be happy to discuss the workflow design and recommend the best architecture before development begins. Best Regards, Hasnain Raja AI Automation | DevOps Engineer | Full Stack Developer