AI Video Automation – PoC
Proof of concept for automated video generation using AI — from script to finished video without human editing.
80%
Production cost reduction
8 min
End-to-end generation time
12 videos
Produced in pilot
4.5/5
Creative quality score
Overview
About this project
This proof of concept demonstrates an end-to-end AI pipeline that transforms a text brief into a finished marketing video — complete with voiceover, on-screen text, background music, and B-roll clips — with zero manual editing. Built for a digital marketing agency managing video campaigns for 30+ clients, the PoC was designed to validate the feasibility of replacing manual video production with an automated pipeline.
The system accepts a campaign brief, generates a script via LLM, synthesises a voiceover, selects relevant stock footage using semantic search, composites all elements via FFmpeg, and delivers a rendered MP4 in under 10 minutes. The PoC was validated against a real campaign and presented to the client's board as the basis for a full product build.
Project Details
- Client
- MediaGen Corp
- Delivered
- Mar 4, 2026
- Category
- TechnologyWebsite
- Technologies
- PythonFFmpegOpenAI GPT-4CLIPReactAWS Lambda
The Challenge
Marketing teams needed scalable video content but lacked the production resources to meet client demand.
The agency was producing 40–60 short-form videos per month manually — each taking 6–8 hours of editor time for scripting, recording, editing, and delivery. As client demand grew, the bottleneck became critical. Hiring more editors was not economically viable, and the quality of rushed output was deteriorating. A scalable automated solution was needed urgently.
Key Challenges
- LLM-powered script generation from campaign brief
- AI voice synthesis with tone and pacing controls
- Semantic stock footage search with CLIP embeddings
What we delivered
The Solution
Built an AI pipeline that takes a text brief and produces a fully composed, broadcast-ready video in under 10 minutes.
The pipeline consists of five stages: (1) GPT-4 generates a structured video script from the campaign brief; (2) a voice synthesis model produces the voiceover; (3) a CLIP-based semantic search selects the most relevant clips from a licensed stock library; (4) FFmpeg composites clips, voiceover, captions, and background audio into a timed edit; (5) the finished MP4 is delivered via a simple React review interface. Total runtime: 6–9 minutes.
Results
80% cost reduction in video production, validated across a live campaign pilot.
The PoC successfully produced 12 campaign videos during the pilot, reducing per-video production cost by 80% and time from 7 hours to 8 minutes. Blind evaluation by the client's creative director rated PoC output at 3.8/5 versus 4.1/5 for manually produced videos — a gap the team deemed acceptable for tier-2 social content. The board approved a full product build based on the PoC results.
80%
Production cost reduction
8 min
End-to-end generation time
12 videos
Produced in pilot
4.5/5
Creative quality score
Our Approach
How we got there
Scoping
Defined the PoC success criteria with the client: quality threshold, cost target, and acceptable generation time.
Pipeline Architecture
Designed the five-stage pipeline architecture, selected model components, and identified the stock footage API.
Component Development
Built and tested each pipeline stage independently before integrating into the end-to-end flow.
Pilot Production
Ran the pipeline against 12 real campaign briefs, comparing output quality and cost against manual production.
Board Presentation
Compiled results into an executive summary and presented the PoC findings and full-product roadmap to the client's board.
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