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AI Content Production Systems

Turn Your Content Workflow Into a Scalable AI Production System

We design AI-assisted video pipelines that connect research, scripting, voice generation, video production, review stages and publishing, so your team can produce more content without managing more freelancers.

Book a Free Pipeline Audit See How the System Works
Stack: n8n · Baserow · TTS · Rendering APIs
Built for: YouTube · Shorts · TikTok · Reels
Live system
▶ hover to play

Screen recording of the actual n8n
production pipeline, not a mockup.

Full pipeline walkthrough · live n8n system
The Problem

Content output is capped by coordination, not creativity.

Most teams scale content by adding people: a scriptwriter here, an editor there, a VA to track deadlines. Every handoff is a place where things stall.

  • Research, scripting and editing live in separate tools with no shared record of status.
  • Freelancer handoffs mean re-explaining context on every single video.
  • Nobody can see what's stuck, what's approved, or what's ready to publish.
  • Quality depends on which freelancer picked up the job that week.
The Shift

Same inputs. A completely different system.

What coordination chaos actually costs you
Then the system takes over.
The System

One connected pipeline, start to finish.

Every stage hands off automatically, with a human review checkpoint before anything publishes.

Content Input
topic, brief or brand goal
Research
source gathering, angle selection
Script
AI-assisted draft, on-brand tone
Voice
text-to-speech generation
Visuals
scene generation & sourcing
Rendering
assembly, captions, pacing
Review
human approval checkpoint
Delivery
status-tracked, ready to publish
TRIGGER n8n: Schedule / Webhook Baserow topic queue / status AI Script Model draft + brand prompt Text-to-Speech voiceover render Visual Generation image / scene API Render Service FastAPI: assembly + captions Storage / CDN rendered output bucket Human Review approve / reject / revise Status Tracking Baserow: DONE / ERROR writes back status Reflects the general shape of a real deployed workflow. Node names simplified. Exact prompts, credentials and internal service names are not shown.
Why It Works

Built to scale output without scaling headcount.

Four properties of a connected pipeline that a folder of freelancers can't replicate.

Scalability

Add more topics or channels without adding more coordination overhead. The pipeline absorbs the volume.

Consistency

Every video follows the same structure, tone and quality bar because it runs through the same system, every time.

Human review

Automation handles the repetitive work; a person still approves what goes out. Nothing publishes unreviewed.

Multi-channel

One input can be reshaped for long-form, Shorts and vertical formats without redoing the work from scratch.

Kemal Gilic, founder of Gilic Systems
Who's Behind This

Hi, I'm Kemal.

I design and build every pipeline you see on this page myself, from the first n8n node to the final rendered file. Background in industrial engineering (Westfälische Hochschule) and technical project management at Bosch and Accenture Interactive, now applied to content production instead of factory floors.

Based in Bali, working with teams across Southeast Asia and Europe. I build the systems myself, run them myself, and I'm the one on the call if something breaks. No account manager between you and the actual work.

Case Study

A multi-niche faceless video pipeline, built and running.

Real interfaces from a deployed system, not a mockup.

3content niches
12/wkplanned video output
n8nautomation engine
Baserowproduction database

Topics are queued and tracked in a structured database, then move through AI-assisted scripting, text-to-speech voiceover generation and a rendering workflow, with every job's status visible end to end, from STARTED to DONE.

n8n workflow showing the faceless video automation pipeline

Fig. 1. Automation workflow: topic pull → script → voiceover → image generation → render handoff.

Production database tracking video topics and output status

Fig. 2. Production database: every topic tracked from queue to finished video URL.

Selected interfaces have been anonymized to protect confidential project information.

Portfolio

Output from the pipeline.

Finished videos produced end-to-end through the system, across both vertical and horizontal formats. See how the pipeline behind them works.

Individual pieces from this system are also available as freelance/work-for-hire collaborations on a per-project basis, get in touch.

Creative Experiments

Technical rendering tests, not client deliverables.

Exploratory work pushing the image-to-video rendering side of the pipeline. Shown separately from production output above.

For Video Production Agencies

Automate the Operational Work Around Your Creative Production

Connect client briefs, asset checks, project setup, production statuses, approvals, revision tasks, multi-format versions and final delivery, without replacing your existing editors, producers or review platform.

Client Brief
Asset Check
⚙️
Project Setup
Production Tracking
Client Review
Revision Tasks
Versioning
Final Delivery

Rush Project Coordination

Tight-deadline jobs tracked and routed automatically, so nothing waits on a manual status check.

Review-to-Task Automation

Client feedback turns directly into assigned, trackable revision tasks, no manual re-typing of notes.

Multi-Version Delivery Workflows

One finished edit reshaped and delivered across every required format and platform spec automatically.

See the Full Agency Workflow →
Services

Three ways to work together.

Start with an audit, get a custom pipeline built, or hand off production entirely.

Content Pipeline Audit

Fixed scope · 1 week
  • Map your current content workflow end to end
  • Identify the bottlenecks costing you output
  • Written recommendation with a concrete next step
  • Live walkthrough call
Book This

Custom AI Content Pipeline

Project-based
  • Full pipeline design: research → script → voice → video → review
  • n8n automation build on your infrastructure
  • Baserow (or equivalent) production database
  • Human review checkpoints built into the flow
  • Handoff documentation and training
Book This

Managed AI Video Production

Monthly retainer
  • Pipeline built, run and maintained for you
  • Ongoing topic sourcing and script review
  • Ongoing status reporting
  • Scoped video volume per month
Book This
Who This Is For

Built for teams producing content at volume.

Faceless channel operators

Running one or more channels solo

Content & marketing agencies

Producing for multiple clients

Coaches & personal brands

Need consistent output, less time

Course creators

Turning expertise into video at scale

Multi-channel companies

Recurring content across platforms

The Difference

Fragmented production vs. a connected pipeline.

Traditional / fragmented

  • Separate freelancers for script, voice, edit, each a handoff
  • Status lives in someone's memory or a scattered chat thread
  • Quality shifts depending on who's available that week
  • Scaling output means hiring and managing more people

Connected pipeline

  • One system carries the work from input to delivery
  • Status tracked in a shared database, visible to everyone
  • Same structure and review bar on every single video
  • Scaling output means adjusting volume, not headcount
How We Start

Five steps from audit to running pipeline.

01

Pipeline audit

We map your current workflow and pinpoint exactly where output is getting lost.

02

Architecture design

We design the pipeline stages, tools and review checkpoints for your specific content and volume.

03

Build & connect

We build the automation, connect the database, scripting, voice and rendering stages together.

04

Test with real content

The pipeline runs on real topics from your niche, with review checkpoints validated before scaling up.

05

Handoff or manage

You take it over with documentation, or we continue running it as a managed service.

FAQ

Questions we get asked.

No. The pipeline handles the repetitive first pass (research, drafting, voice, assembly), so your people spend their time reviewing and directing quality instead of doing every step manually.

Typically n8n for automation, a structured database like Baserow for status tracking, an AI model for scripting, a text-to-speech service, and a rendering pipeline, configured to your existing stack where possible.

Yes. The same input can be shaped into long-form and vertical formats without redoing the underlying research and script work.

Every pipeline includes at least one approval checkpoint before publishing. We design where that checkpoint sits based on how much oversight you want.

The Pipeline Audit is a fixed, free first step. We'll confirm scope and any next-step pricing on the call.

Ready to see where your pipeline is leaking output?

Book a free audit. We'll map your current workflow and show you exactly where a connected pipeline would change things.

Book a Free Pipeline Audit See How the System Works
Get In Touch

Book your free pipeline audit.

Tell us about your current content workflow: channels, volume, where it's breaking down. We'll follow up to schedule the audit call.