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How We Slashed 70% of a Media Company's Manual Workload with Three Production AI Systems

A Singapore media company was drowning in 60-minute video QC sessions, 6-hour content repurposing cycles, and fragmented analytics. As Founding Engineer, we architected three production AI systems that now run their daily operations, freeing the creative team to actually create.

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Key Results

0%Workload Reduction
0%QC Time Saved
0Production AI Systems

The Challenge: Scaling Content Without Scaling Headcount

CrazyTok Media was winning. Revenue up. Content volume exploding. But their operations couldn't keep pace. Every video meant 60+ minutes of manual QC. Every podcast episode meant 4-6 hours of content repurposing. Analytics lived in a dozen fragmented dashboards with no unified view.

The operational bleeding:

  • 60+ minute video QC sessions: Manual frame-by-frame review for text overlays, audio sync, and brand compliance
  • 4-6 hours per content repurpose: Transforming one podcast into Twitter threads, blogs, and short-form clips consumed entire days
  • Analytics chaos: YouTube metrics scattered across dashboards, PRE/POST comparison nearly impossible
  • No quality enforcement: Netflix-level standards existed on paper, but manual review couldn't consistently enforce them
  • Linear scaling trap: Every new content piece required proportional increases in human labor, a death spiral at scale

Executive Axiom

Media companies face a brutal choice: scale headcount linearly with content volume, or build AI systems that break the linear relationship. Manual operations that consume hours per asset become impossible at 100+ pieces monthly. The math doesn't lie.

Break the Linear Trap

The Solution: We Architected Three Production AI Systems from Scratch

As Founding Engineer, we designed, built, and deployed three distinct AI automation systems, each targeting a critical operational bottleneck. These aren't prototypes. They're production systems running daily operations.

System 1: Deployed AI-Powered Video QC with Netflix Standards

  • Engineered LLM-based text detection system identifying on-screen overlays, spelling errors, and brand violations
  • Architected multi-stage pipeline: frame extraction → OCR → LLM interpretation → compliance scoring
  • Integrated industry-standard quality checks matching major streaming platform requirements
  • Impact: 60+ minutes → 5-10 minutes per video (83-92% efficiency gain)

System 2: Constructed Podcast → Social Content Pipeline

  • Architected 4-stage AI workflow: chunking → interpretation → tweetification → editing
  • Engineered 500+ line LLM prompts for consistent brand voice across all outputs
  • Built AirTable integration for content management and team review workflows
  • Automated transformation: one 60-minute podcast → Twitter threads, blogs, short-form scripts
  • Impact: 4-6 hours → 20 minutes per episode

System 3: Built YouTube Analytics Chrome Extension

  • Developed custom Chrome extension for YouTube Studio with automated PRE/POST treatment comparison
  • Constructed 35-column data export: views, CTR, watch time, traffic sources, engagement metrics
  • Created cross-platform aggregation comparing performance across YouTube, Twitter, LinkedIn
  • Impact: 2+ hours → 5 minutes for comprehensive analytics reporting

Deployed Additional AI-Powered Tools

  • Profile matching: Image recognition via Playwright and Pillow for cross-platform guest identification
  • Headline generators: LLM-powered title and thumbnail optimization for maximum CTR
  • Content workflow automation: End-to-end pipelines from raw footage to multi-platform distribution

Engineering Philosophy

These aren't prototypes. They're production systems handling daily operations for a scaling media company. Every system was engineered with error handling, quality validation, and team workflows baked in. The 70% workload reduction didn't eliminate jobs. It eliminated grunt work.

The Results: 70% Workload Eliminated, Creative Team Unleashed

All three systems launched August 2024 through present, now running as core operational infrastructure:

  • 70% manual workload obliterated: Content team freed from hours of repetitive QC, repurposing, and analytics work
  • 83-92% video QC efficiency: 60+ minutes → 5-10 minutes per video
  • 93% content repurposing acceleration: 4-6 hours → 20 minutes per episode
  • 96% analytics time reduction: 35-column reports in 5 minutes vs. 2+ hours manual compilation
  • 10x content multiplication: Single longform asset → 10+ platform-specific pieces automatically
  • Netflix-level enforcement: Automated quality standards no longer dependent on human vigilance
  • Data-driven iteration: Real-time analytics enable rapid content strategy pivots

Executive Axiom

AI automation doesn't replace creative teams. It eliminates the grunt work choking them. A 70% workload reduction doesn't mean 70% fewer people. It means 10x more output with the same team. The creative work gets done by humans. The repetitive work gets done by machines.

Unleash Your Creative Team

Technical Stack

  • AI & LLMs: OpenAI GPT-4, 500+ line prompt engineering, multi-stage AI workflows
  • Computer Vision: Playwright, Pillow (PIL), OCR for image recognition and text detection
  • Automation: Python, AirTable API, Chrome Extension development (JavaScript)
  • Content Processing: Video frame extraction, audio transcription, text chunking and transformation
  • Analytics: YouTube Studio API, cross-platform metrics aggregation, data export automation

Your Content Team Is Drowning in Grunt Work

If your team is burning hours on manual QC, content repurposing, or analytics compilation, you're wasting their talent. We build production AI systems that eliminate the repetitive work and let your creative people create.

Free Your Creative Team