Celestia Intelligence
Celestia measures what people say and do around an idea, then turns it into a clear read on what to make, where to launch it, and who will show up for it. It reads the same way for a studio slate as for a creator’s channel.
Domestic-power themes resonate loudly with thriller audiences; comp validity and talent momentum are the weak legs — refine packaging before greenlight math.
Signal-strength reading of external/audience-side data. The producer makes the creative Develop / Refine / Pass call.
How much to trust the read above — a gauge on the analysis, not part of it.
Audience chatter around domestic-worker power dynamics is loud, current, and majority-positivec1c2. The concept's genre lane — the female-led domestic thriller — is rising on both behavioral and conversational signalc5.
The main liability is the comp slate: two of the four anchors are prestige outliers whose audience profile does not transfer to this packagec6c7. Talent momentum is flat rather than falling, which reads as neutral for packagingc8.
Primary risk
Primary opportunity
A film commits its budget before there's any real evidence an audience exists. A creator commits weeks of production time and finds out from the analytics, after the video is live. Different pipelines, same blind spot. Celestia puts the evidence in the room while it can still change the decision.
Projects move forward before clear audience and market evidence is available.
Demand, cultural shifts and audience momentum are spotted too late to act on.
Campaigns go broad without knowing who is genuinely interested or which message will land.
Two kinds of evidence, read together. One explains the attention; the other shows where it's actually going.
Posts, comments, reviews, threads, press. Something a person chose to write. It explains the attention.
Searches, views, tickets, ratings. Nobody is asked anything; behaviour is simply counted.
Default weighting
Adjusted per project
30Say
Do70
Behaviour carries more weight because it sits closer to real attention. This is a starting weight, not a fixed rule. It moves with the project, the market and how much data actually came back.
Describe the concept, attach the script if there is one, name the comps. Back comes one connected read, and every claim in it links to the source it came from.
Examples
Title
Logline
Drop script or browse
PDF · DOCX · Fountain · TXT · MD — max 5MB
Genre
A logline is enough to start. Attach the screenplay and it reads the themes out of the script itself, then goes looking for the audience those themes already have.
Scripts are processed server-side, never used to train a model, and deleted after 24 hours.
Sentiment across topics
Momentum across topics
How we measured — 2 vectors · 3 anchor works · filter kept 35/47
Thin sample after filtering — read as directional, not conclusive.
How we measured — filter kept 23/32
Structural comp: same engine (housekeeper POV + intimate threat), comparable scale.
Silent
Loud
Aspirational, not structural — usable as a thematic reference, not for greenlight math.
Silent
Loud
Signal volume by platform
By platform
What to make, where to launch it, who to reach. Each one changes the other two, which is why Celestia treats them as a single question, whether the project is a feature film or next month's flagship video.
Whether the audience for this idea already exists, and how warm it is.
Which markets and moments the demand is actually concentrated in.
Which audiences to spend against, and which angle they respond to.
Celestia starts in film, where each decision carries the most money. The same engine reads for anyone whose next release is a bet on an audience.
Slate and greenlight calls with the comp evidence checked instead of assumed, and a paper trail for every claim in the room.
Where the demand for a title actually sits, which markets are warm, and when a release meets the audience instead of chasing it.
YouTubers, podcasters, writers. What to make next, when to drop it, and which angle your audience is already asking for.
Bring a project you’re weighing right now and we’ll run it live.