Audience reception, predicted

Know how audiences will receive your film.
Before anyone sees it.

An AI that watches your actual footage - the whole film, start to finish - and predicts its real-world reception: where engagement holds, where it fades, and what to fix first.

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An iScreeningRoom product
The problem

Testing a film has always meant showing it to strangers.

Every human screening in this industry is a leak surface - a piracy risk. We should know. In 10+ years of running iScreeningRoom test screenings, we've never had a film leak - and it hasn't been easy. Burned-in watermarks, floating watermarks, NDAs, audience authentication - on every screening. For some filmmakers, however, even that pristine record hasn't been enough to trust an online test screening.

But that's human testing: exposure managed, never exposure removed. The irony is that the films with the most at stake test the least. And the ones that do test, test once - not ten cuts, not every ending. Once.

So, what if you could test your film without ever showing it to a test audience - as many times as you like, unlimited cuts, privately, at a fraction of the cost?

You can.

The collaborator in the room

Meet Felix.

The collaborative cinephile in your editing room - and the only collaborator with nothing to lose by telling you the truth.

After the evaluation, you work with aiScreeningRoom’s Felix on your completed report. Straight talk on what’s working, what’s not working, what to fix, and how to fix it - with the craft fluency and film-history parallels of a lifelong cinephile, from someone who watched every frame of your cut and can cite the moment he means down to the second.

Every note you’ve ever gotten in post came with an incentive attached. Executives push their bias. Financiers protect the check. Single-theater paid audiences measure whoever showed up that night. Today’s AI assistants are trained to please - agreeable by default, flattering on request. Felix is none of them. He has nothing to lose by telling you the truth - and he couldn’t soften the verdict if he wanted to. The score is the score: not up for renegotiation by the executive, the financier, or even you.

“We can’t fake anything. If a scene isn’t landing, we’re going to talk about it. If the lighting needs work, we’re going there.”

Felix
How it works

Three steps between your cut and its verdict.

01

Upload your cut

Bring a film at any stage of post - a rough assembly or a locked picture. Every cut can be tested.

02

The AI watches the entire film

The footage itself, start to finish - not a synopsis, not a summary. What plays on screen is what it reads.

03

Receive the verdict

A predicted audience rating with a range across independent viewing passes (pass-to-pass variation - not a full error bar on the film). A minute-by-minute read of where your film holds them and where it loses them - down to the act, the scene, the second. What your natural audience will praise, what they'll pan, and the single most impactful change to make before picture lock.

The report

What comes back after the watch.

The verdict
The timeline
Felix on the cut

What changes

No recruited viewers. No screeners in circulation - and nothing limits how often you test.

No test-audience leak surface

No recruited strangers, no phones, no screeners in circulation. Testers never see the film, so they cannot leak it.

Test every cut

Recut in the morning, test in the afternoon, compare the verdicts side by side. Testing stops being an event and becomes part of the edit - every version, every day, with no extra test-audience exposure.

Know first

The verdict arrives while you can still act on it - before festivals, before buyers, before the public.

Why trust it

Built by iScreeningRoom - “a revolutionary online test screening platform” (Forbes) - on years of real audience test screenings.

aiScreeningRoom is calibrated and validated against iScreeningRoom's screening corpus: more than 35,000 survey responses and nearly 43,000 timestamped, moment-by-moment audience reactions from real test screenings of real films.

iScreeningRoom panels landed within one IMDb point on 89% of 36 qualifying films, each film graded by a mapping that never saw it. Separately, on 11 films locked away from training and tuning, the AI's average miss against those panels was 0.253 on the 1 to 5 panel scale, as of September 2026.

Filmmakers deciding between cuts. Producers choosing an ending. Distributors pressure-testing an acquisition. Sales agents pricing a title. One instrument, before the world weighs in.

We publish how we validate. Nothing is taken on faith.