Automation / AI content factory for creating short videos

Budget: 2000 UAH Deadline: 2 days

Hello!
We are the Business Atlas team, official partners of n8n. Creating a modular AI content factory for unique Reels/TikTok instead of banal templates is a powerful challenge, and we are implementing it 100%.
The essence of your project hinges on three critical nodes:
The first — dynamic scripting and memory. Setting up multi-step prompting in n8n (OpenAI/Claude) with a database (Airtable/PostgreSQL). It will store the history of topics and locations so that the AI analyzes past videos and generates new plots each time without repeats.
The second — content generation and consistency. For unique videos, we will set up dynamic style mapping, and for the "AI blogger" mode — work with stable Face ID (Midjourney + InsightFace / Flux with LoRA), where only clothing and surroundings will change.
The third — animation and modular assembly. Integration via API of video generation and lip-sync services (HeyGen, Kling, Runway, or LivePortrait) with auto-editing of scenes and subtitle overlay in the final vertical video.
My experience as a project manager and my team's experience focus specifically on AI automation and low-code architecture. We have implemented over 50 projects in the UA/EU markets, including autonomous AI SMM agents for Telegram. As n8n partners, we will deploy a self-hosted system on your VPS — this will allow processing gigabytes of media files without monthly subscription fees for platform limits.
Proposal and answers to questions:
Stack: GPT-4o/Claude (text), Midjourney/Flux (photo), ElevenLabs (voice), HeyGen/LivePortrait (video/lip-sync).
Character: Fixation of prompt-seed + Face Swap API for 100% face preservation in any scenes.
Cost per video: Approximately $0.30 to $1.50 per minute (depending on the chosen video API).
MVP (Stage 1): n8n checks the database for duplicates, generates a unique script, photo, voiceover, and lip-sync, outputting ready scenes or basic edits. Effects and auto-posting will be in the next stages.
Timeline: MVP development — 3–5 weeks. The exact estimate will be fixed after a short diagnosis, where we will choose the final stack of models according to your budget.
Message me privately — let me know what specific content theme is planned to start, and we will agree on a time for a quick call! Expand

Budget: 10000 UAH Deadline: 14 days

Good day! I was working on automating content generation in Python — linking GPT for ideas and scripts, breaking down into scenes, generating images frame by frame, and stitching them into a video. To ensure the videos are not uniform, I maintain a bank of themes plus randomization of scenes, styles, and structure — this is key for you. I am ready to assemble such a pipeline, approximately 2 weeks for a working MVP. We also automate voiceovers and subtitles, or is the video currently without voice?

Budget: 10000 UAH Deadline: 13 days

Application for "Automation / AI Content Factory for Creating Short Videos":

Hello! I am building AI automation on n8n, including content generation chains through multiple APIs simultaneously, so this modular approach is familiar to me.

How I see the architecture:

Idea and script generation: LLM (GPT or Claude) with a database of already used topics/stories (stored separately, for example in Google Sheets or Airtable), so the system avoids repetitions and builds a new idea considering the history.
Scene breakdown: the script is divided into individual shot descriptions through the same LLM call, each description is immediately formatted into a prompt for image generation.
Image generation: a separate node with the ability to switch providers (Midjourney API, Flux, or another of choice), with a fixed reference character for the AI blogger mode through image-to-image or consistent character seed.
Bringing scenes to life with speech: priority to models that immediately provide image-to-video with lip-sync (for example Kling, Hedra, or similar), with a fallback to separate voice generation + animation if it turns out cheaper.
Assembly: connecting scenes, subtitles, music is a separate module that can be activated step by step.
Publishing: a separate step on TikTok/Instagram API, also connected later.

Each block as a separate n8n module, so replacing the LLM, image generator, or voice service does not break the entire chain.

Regarding character consistency: keep fixed reference images and a prompt template with a description of appearance, rather than relying solely on the seed.

I suggest starting with Stage 1 (content factory to ready scenes/videos), assessing the actual cost of generation on 5-10 test videos, and then calculating editing and auto-posting separately.

How many videos per day/week do you plan to generate at the start - this will directly affect the choice of models based on cost? Expand

Budget: 1000 UAH Deadline: 1 day

Hello
write to me, I will do it
I have a project like this in progress
collecting nodes and n8n is not difficult, the whole complexity is in the prompts, write everything, I will do it
I am making a video with seedance
I will show what comes out
the cost of the video for myself

Budget: 18000 UAH Deadline: 15 days

The task is clear: not a template generator, but a full-fledged content factory - a system that regularly creates videos for TikTok and Instagram Reels with different plots, scenes, and visuals, without repeating ideas and structures.

I am building this as a Python orchestrator: the LLM generates a unique idea and script with memory of past themes (embedding search through history to avoid repetition), breaks the script into scenes with descriptions and prompts for each, then generates images or videos for the scenes via API (Runway, Kling, Pika, or whatever you prefer based on the budget for models), and assembles the final video using ffmpeg. A task queue with retry logic allows for scaling production without manual intervention.

Regarding N8N in the category tag: I prefer a Python service instead of no-code for the content factory with state - it provides more control over the generation queue, deduplication of ideas, and model replacement under the hood. If N8N is essential as a high-level orchestrator - a hybrid approach with a custom service for heavy logic is possible.

The cost of generating a video depends on the chosen APIs (image-to-video services vary in price) - I will clarify after a brief discussion about the budget for models.

Budget: 20000 UAH Deadline: 10 days

Hello! The project is large-scale and incredibly interesting. Creating not just a "template," but a flexible content factory with memory and uniqueness control is the only viable way to generate quality AI traffic in 2026.

I lead the digital agency KenoStudio. We build development and automation based on AI-driven system principles. We actively work with n8n, databases (Supabase/PostgreSQL), and advanced generative APIs, so we understand how to design a flexible and scalable architecture for your task.
Proposed system architecture (based on n8n)

We will build a modular workflow in n8n, where each step can easily be replaced with another neural network via API.

Idea generation and repetition control:

LLM (Claude 3.5 Sonnet / GPT-4o): Generates the script, scene layout, and detailed prompts.

System memory: We will connect Supabase (PostgreSQL). Before generating a new idea, the LLM queries the database, analyzes the history of the last 50-100 videos, and removes repetitions of plots or phrases.

Image creation and character consistency:

For different characters: Generation through FLUX.1 (via Replicate/Fal.ai) - this is currently the best model for detail and caption text.

For a permanent AI blogger (Consistency): We will implement a two-step pipeline. First, we generate the scene with the desired emotion and angle, and then we overlay the face of your permanent character using a quality face-swap API (e.g., InsightFace / ReActor on the server) or use IP-Adapter / LoRA technology to preserve facial features.

Bringing to life and voice:

Voice: ElevenLabs (the best natural voices supporting Ukrainian and Russian languages with correct intonations).

Lip-Sync / Animation: Using LivePortrait or SadTalker API to overlay facial expressions and synchronize lips on the generated portrait to the prepared audio track. This is significantly cheaper and more accurate than generating a full video from scratch in HeyGen.

Automatic editing (FFmpeg / Shotdeck API):

The script automatically stitches the obtained video scenes, overlays the audio track, generates subtitles based on the script text, and adds royalty-free background music.

Economics and development

The cost of one video (API expenses): About $0.30 - $0.80 per finished video (the main expense goes to ElevenLabs and video/face-swap generation). This is much more cost-effective than ready-made platforms. Expand

Budget: 27000 UAH Deadline: 18 days

Hello, Valery!

Experience: 2+ years training custom Stable Diffusion models and LoRA (since the early SD era) - produced monetized AI animation content for TikTok. So mode 2 (a constant AI blogger with a recognizable appearance in different situations) is exactly what is solved by LoRA training on a specific character: you train LoRA once on the desired appearance, then generate scenes with different environments/clothing/actions, while the face and features remain consistent. This is more reliable than relying solely on prompts for consistency.

n8n: I have no direct production experience, I honestly say this right away. I prefer to build architecture with code (Python) - for a content factory with state (history of videos, control of idea repetitions, modular model replacement) this gives more control over the generation queue and retry logic than no-code scenarios, but it takes longer to start from scratch than with ready-made n8n. If n8n is mandatory - I can offer a hybrid: n8n as a top-level orchestrator, a custom service under the hood for heavy logic (consistency, deduplication of ideas).

Architecture: LLM (Claude/GPT) generates the topic → script → scene-by-scene breakdown → image model (SD/LoRA for a consistent character, or Midjourney/Flux for mode 1 with different heroes) → image-to-video/talking-head service (Kling, Runway, HeyGen - depending on the budget for generation) → assembly. I store the history of already created topics/scenes in a database with embedding search (I did something similar in youtube_helper - FAISS + hybrid retrieval) to avoid repeating ideas.

The cost of generating one video heavily depends on the chosen APIs (image-to-video services vary in price) - I will provide an exact estimate after a brief discussion of the budget for the models.

MVP (stage 1): a working content factory up to ready scenes/videos without editing - approximately 15-20 days, I am ready to discuss the development cost after clarifying the volume (how many videos/scenes in the MVP, which of the two modes is a priority). Expand

Budget: 1000 UAH Deadline: 1 day

Hello!

I have extensive experience in creating automated systems for working with various social networks. I am ready to develop a system for you that will perform the listed tasks.

I suggest we discuss the details in private messages.

Budget: 20000 UAH Deadline: 15 days

Hello!
The problem here is not only in generating videos but in building a scalable architecture that will allow easy changes to AI models and avoid content repetition. I would suggest implementing this as a modular system on Make.com with integration of OpenAI/ChatGPT, Midjourney, ElevenLabs, and other AI services via API, so that each stage can be improved independently.

In similar projects, I have built AI automations that combined content generation, AI data processing, and integration of various services into a single workflow. I also have experience in creating AI bots, automated marketing systems, CRM integration, and building end-to-end processes through Make.com, which allows scaling solutions without manual work.

For this project, I envision the following architecture:
• generation of topics and scripts through ChatGPT;
• saving the history of ideas to control repetitions;
• image generation through Midjourney/API;
• voiceover through ElevenLabs;
• modular integration of services through Make.com;
• the ability to easily replace LLM, image generator, or voice service without rebuilding the entire system.

The first MVP can focus on the complete cycle from idea generation to finished scenes, while automatic editing and auto-publishing can be added as separate stages.

It would be interesting to discuss which AI services you have already tested, what budget you plan for generating one video, and whether there is a need to run several thematic content streams simultaneously. Expand

Budget: 25000 UAH Deadline: 14 days

Good day! We have experience in building pipelines for video generation using the APIs of neural networks such as OpenAI, ElevenLabs, and HeyGen. We implement this through custom scripts in Python that automate the editing and publishing of content. The system will operate autonomously, providing a stable flow of videos for your platforms. We are ready to discuss the details of implementation.

Budget: 23000 UAH Deadline: 7 days

Hello!

I have experience in developing AI automations in n8n: multi-step workflows, LLM, API, Telegram, Google Sheets, data processing, and business logic.

For your project, I would suggest a modular architecture:

LLM generates ideas, scripts, and breaks them down into scenes;
prompts and images are created for each scene;
scenes are animated through an image-to-video API;
voice and lip-sync are generated by one model or separate services — after comparing quality and cost;
the history of the videos is stored in Supabase/PostgreSQL to check new ideas for similarity and reduce repetitions;
n8n is used as the main orchestrator.

For a permanent AI character, reference images and models with character consistency support can be used. If the basic solution is insufficient, separately test LoRA.

In the first MVP, I propose to implement:

selection of niche, language, duration, and character mode;
generation of several ideas;
checking for repetitions;
creation of scripts and scenes;
generation of images;
animation of scenes;
saving materials;
regeneration of individual scenes;
accounting for generation costs.

Editing and auto-posting can logically be moved to the next stages.

The preliminary cost of a video lasting 20–30 seconds is about $5–15, depending on the number of scenes, model, and number of regenerations.

I suggest starting with a technical prototype of the full chain on 2–3 test videos. The cost of the prototype is $500. After testing, a full MVP can be accurately assessed. Expand

Budget: 1000 UAH Deadline: 1 day

Good day, Valery.

The diversity of content is the most challenging part of such systems: without controlling repetitions, LLM quickly collapses into monotonous plots. Your factory will operate on n8n with a modular architecture, where each stage (idea → script → scenes → images → video → assembly) is a separate node that can be replaced without rewriting the entire pipeline. To avoid repetitions, PostgreSQL with pgvector will be used: each generated idea is stored as an embedding, and before creating a new one, the system checks the semantic distance to previous ones — this way, the plot does not repeat even during mass generation.

The consistency of the AI blogger is the second critical point, and it is worth starting with a technical pilot before fixing the architecture. Stable Diffusion with LoRA training on 15–20 images of the character provides more stable face retention between clips than Midjourney via API, but requires its own inference server. An alternative is reference images through ControlNet, which is cheaper but has less stability. The decision is made after comparing both approaches on real scenes from your niche.

For voiceover in Ukrainian and Russian, the optimal balance is Azure TTS or ElevenLabs with subsequent lip-sync through models like SadTalker/Hallo. The combination of separate TTS + animation is cheaper than comprehensive solutions like HeyGen, but falls short in the quality of mimicry. Your architecture supports both options through modularity — you can start with the cheaper one and replace the module without changing the rest of the system.

Automated editing and auto-posting are separated into distinct stages, as you suggested.

Options:

MVP Content Factory
10,000–14,000 UAH; ≈13 days
- Automatic generation of unique scripts through LLM
- Creation of images for script frames
- Voiceover of text and basic face animation (lip-sync)
- Modular structure in n8n for replacing AI models

Full Cycle
22,000–30,000 UAH; ≈20 days
- Everything from the previous option
- AI blogger mode with character appearance retention
- Automatic editing: scene stitching, music overlay, and subtitles
- Repetition control system to ensure content diversity
- Ready-to-publish vertical video file

Enterprise Automation
35,000–45,000 UAH; ≈25 days
- Everything from the Standard package
- Automatic posting to TikTok and Instagram Reels
- Expanded content history database for analysis and avoiding duplicates
- Cost optimization for generation (hybrid voiceover and animation schemes)
- Priority support and customization for different niches Expand

Budget: 20000 UAH Deadline: 21 days

Valery, to create a true AI content factory, it is necessary to set up a pipeline where each stage of idea and visual generation has variability through dynamic prompts, rather than static templates. The main challenge here is ensuring visual consistency of characters and scenes amidst the diversity of scenarios.

My strategy is to build an architecture based on LLM connections for script logic and API generative models for visuals, where each step relies on a constantly updated knowledge base. This will allow the system to avoid repetitions and create unique plots for each iteration.

At what stage do you plan to implement editing and voiceover overlay in this system, or is there a need for integration with third-party services for automatic collection of final videos?

Budget: 20000 UAH Deadline: 7 days

Hello.
I have worked on similar projects.
I will try to achieve the best result in the shortest time.

Budget: 25000 UAH Deadline: 5 days

Hello, Valeriy.
I have done similar projects — I know the nuances and will do exactly what is described. There are a few clarifications before starting.
The final price/timeframe after all clarifications.

Profile: Freelancehunt
Reviews: Freelancehunt

Budget: 1000 UAH Deadline: 1 day

Good day, I am ready to complete your task quickly and efficiently. I have extensive experience in creating various bots. Please write to me in private messages to discuss the details. I would be happy to help :)