By clicking “Accept”, you agree to the storing of cookies on your device to enhance site navigation, analyze site usage, and assist in our marketing efforts. View our Privacy Policy for more information.
WORKED WITH
THE FUNDAMENTAL 
SHIFT

Film production is still built on a high-risk model: Develop  → Shoot → Edit → Hope it works

I change that to the Optimized model: Develop → Simulate → Test → Iterate → Validate → Shoot → Succeed

Before you commit to production budgets, I help you build a near-film prototype — one you can actually watch, test, and refine.

This is not
"AI MAGIC"

This is not a software platform. This is not automation replacing creative judgment. This is not predictive black-box algorithms making decisions.

I lead your team through a structured workshop process. AI is used only to lower execution cost — never to replace creative thinking.
You remain the decisionmaker.
I build the testing environment.

Prototype
the Audience

While the film is being simulated, we build demand in parallel. Not by defining a “target demographic” on paper. By testing real audience response and building fandom. We:
• Identify where your real audience actually spends time
• Release targeted AI-assisted micro-content
• Test hooks, themes, tone, and positioning
• Observe reactions and  engagement
• Refine messaging based on real data.

MEMBER OF, PARTNER & ALUMNI

Maciej Żemojcin

AI FILM TECHNOLOGY CREATIVE ADVISOR

I'm a pioneer of practical application of AI tools in industry level film productions. I'm also  the first virtual production producer in Poland. I have been a technological supervisor in VP and AI for multiple major and independent productions as well as speaker and consultant for Industry Markets from Cannes and Berlinale to Vivatech and Goa FilmBazaar and more.

I'm also an initiator of the mission project “Picture from Auschwitz” creating the first globally Certified Virtual Film Location of Auschwitz-Birkenau Memorial.

I have 20 years of experience in international film production. Technically driven films and technology in storytelling are my passion.

full bio

FAQs

How to optimize film production using AI tools?

Film production still runs on a speculative model:
Develop  → Shoot → Edit → Hope it works
The problem is structural. You only discover weaknesses after you've spent the money. I turn it into optimized model:
Develop → Simulate → Test → Iterate → Validate  → Shoot → Succeed
I work with producers during development to build a near-film prototype — not script coverage, not theory, not market guesswork — but a dynamic cinematic simulation of the film.
We test tone, pacing, emotional arcs, alternate story directions. We stress-test key scenes. We adjust before decisions become irreversible.
This isn’t AI replacing creativity. I lead a structured workshop process. AI is only used to reduce execution cost. Creative judgment stays with the you as producer and your team.

Is AI going to make the film not copyrightable?

I build the testing environment and you still shoot your film, so all the normal copyright lagal rules apply and your IP remains safe.
This is not a software platform. This is not automation replacing creative judgment. This is not predictive black-box algorithms making decisions.
I lead your team through a structured workshop process. AI is used only to lower execution cost — never to replace creative thinking.
You remain the decision maker and producer.

I need creative freedom, why to use this strict technological path?

I absolutely agree. I'm trying to give even more creative freedom to the team. I relocate trial and error from the expensive production stage to the inexpensive development stage.

Creativity Needs Freedom — Not Financial Pressure. Creative work requires exploration to find what you really like. You can play without strict boundaries. The problem isn’t experimentation.
The problem is in which production stage it happens.

You keep creative freedom — without carrying production-level risk.

How do you I test the audience without the film?

I want to build the value of IP of your film. That's why we prototype the Audience. While the film is being simulated, we build demand in parallel.
Not by defining a “target demographic” on paper. By testing real audience response and building fandom. We:
• Identify where your real audience actually spends time
Release targeted AI-assisted micro-content
• Test hooks, themes, tone, and positioning
• Measure engagement and response
• Refine messaging based on real data
• We build your fandom
We don’t imagine a target audience.
We observe who responds to actual content and why.

How much does it cost?

I work as an independent technology and creative advisor. There is no agency overhead — you work directly with me.

Projects can start from €2,500 for a focused workshop, including preparation and analysis. My daily rate starts at €500 per day. The final budget depends on the scope, complexity, and level of involvement required. In practice cost savings generated exceed multiple times my fee. You could say I work almost for free — because my contribution pays for itself.

For me, success is measured by producer's satisfaction and savings but also by the impact on the final audience. If the work strengthens both — we have done it right.

Would you summarize what you do?

Film production is still a high-risk gamble.
You develop, finance, shoot, edit — and only then discover what doesn’t work.
I change that.
Before you commit to production budgets, I help you build a cinematic prototype of your film — something you can actually watch, test, stress-test, and refine.
We move trial and error out of the expensive stage and into development — where mistakes are affordable.
By the time you shoot, creative direction is validated, positioning is tested, and audience demand is already building.
Production becomes execution — not discovery.

Can you share examples of your work?

Because development cycles typically run a year or longer, much of it is either still under NDA or no longer representative. In this field, even work from a year ago can feel technically outdated.

To provide a transparent benchmark, I created an independent sample project: a reinterpretation of the 25-year-old The Lord of the Rings trailer. I used the original trailer as storyboard and I upgraded 100+ shots using contemporary AI workflows to test scalability, consistency, and iteration speed across a full sequence.

The piece was completed in one week. What you see is iteration v.0.1 — the baseline from which we usually efine.