Oraqul
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Plan yourlaunch right.

A culturally grounded AI agent for launch planning in media & entertainment.

Plan it. Check it. Fix it.

Say what you are working on, the way you would tell a colleague. Oraqul works out which job it is.

  • Make a plan

    A plan for each market, worked back from your release date.

    You might type: “Plan the release of Night Ferry in Lagos, London and Houston.”

  • Check my plan

    Every assumption marked as holding, weak or broken, with a stronger option where one breaks.

    You might type: “Check my plan: open in the UK, then Canada.”

  • Fix my plan

    Who actually came, which assumption missed, and a revised plan built around them, before the launch or after it.

    You might type: “It missed. Here are our results by age band.”

Then keep going, in the same project.

See each job in action
  • Find what you missedNearby markets and areas the data points to, with a first test for each.
  • Run the campaignYour calendar as actions to edit and tick off, each with a guide to adapt.
  • Test two anglesAdd your own figures and Oraqul compares them, or says inconclusive.
  • Check what changedAsk again later. Moved findings and dated pages, with your plan untouched.

An agent that does the work, and shows it.

  • Plans its own stepsIt reads your message, decides what to look up, and works one step at a time.
  • Checks its own draftIt compares the plan with what you asked for and rewrites it until it fits, in up to three drafts.
  • Shows its receiptsEach claim links to the exact data behind it, so you can check it.

The product’s own chat, replaying a recorded example.

Built on what real audiences love.

Oraqul gives Qloo what surrounds your launch: comparable titles, places and an age band. Qloo returns what that audience likes across film and TV, music, books, podcasts, games, brands and places. Then code works out the answer with a fixed rule, and the model only writes it up.

An example taste map: two comparable titles in the centre, and around them the series, artists, books, podcasts, games, brands and places their audience also likes, as Qloo ranks them.
Salt RoadThe Glass LanternYour comparable titles

Example: titles go in, what their audience loves comes out. Names are invented. Hover or tap a name.

Measured taste

Every number comes from the data, never from the AI.

Across culture, not one shelf

Your comparable titles go in. What that audience also loves comes out, across series, music, books, podcasts, games, brands and places.

Check any claim

Each one comes with a receipt: the exact data behind it.

Audience taste data from Qloo.

Every place you name gets its own read.

Name Lagos and Oraqul asks Qloo what the audience for your comparable titles looks like there, ranks it against your other cities, and says whether the place fits. Then it goes down to the neighbourhoods.

Lagos

Holds
WeakerAn average cityStronger

The audience is 1.6 times as strong here as in an average city. Open here first.

Strongest around Surulere and Lekki. Screens that rank highest with this audience: Kingsway Screen, Palm Grove Cinema.

Your cities, ranked together

  1. Lagos1.6
  2. London1.3
  3. Houston0.9
  • One comparison. Your cities are ranked together in a single call, so their scores can be compared.
  • Honest about thin data. Where a place has too little to rank, it says so and lowers its confidence.
  • A lead, not a verdict. Neighbourhoods are readings a few kilometres across: leads to confirm on the ground.

Made for six kinds of launch.

Each has its own questions, its own calendar and its own way to read the results.

  1. Film and series

    Release plans for films and series, by territory and opening date.

    • Territory ladder
    • Rival date check
    • Partner brief

    Checked against real audience data

    • Audience fit by age, gender and place
    • Territory ladder, as lift over a neutral audience
    • Rival opening dates, measured as shared audience
    What it reads and what you bring

  2. Music

    Releases and tours, planned city by city.

    • Tour route
    • Support act matcher
    • Sponsor brief

    Checked against real audience data

    • Audience fit by listener type, age and city
    • Tour route, as lift for each stop
    • Support acts compared across the route cities
    What it reads and what you bring

  3. Books

    Launch plans for titles and imprints, by market.

    • Comp shelf
    • Adaptation bridge
    • Outreach brief

    Checked against real audience data

    • Reader audience by age, genre and place
    • Comp shelf, as reader overlap with comparable titles
    • Adaptation bridge to series, film and podcasts
    What it reads and what you bring

  4. Podcasts

    Shows, guests and sponsors, planned around the listener.

    • Topic map
    • Cross promotion shows
    • Sponsor brief

    Checked against real audience data

    • Listener audience by age and place
    • Topic map, as tags rival shows do not own
    • Shows to swap with and sponsors ranked by listener overlap
    What it reads and what you bring

  5. Games

    Fan bases, regions and collabs, planned before launch.

    • Fan base bridge
    • Region ranker
    • Collab brief

    Checked against real audience data

    • Player audience by age and region
    • Fan base bridge to music, series and film audiences
    • Region ranking, as lift over a neutral audience
    What it reads and what you bring

  6. Live shows

    A single show or a short run, planned from the show date back.

    • On-sale plan
    • Rival date check
    • Sponsor brief

    Checked against real audience data

    • Audience fit by listener type, age and city
    • Which of your cities the audience is strongest in
    • Support acts compared across the cities
    What it reads and what you bring

Checked against real audience data

  • Audience fit by age, gender and place
  • Territory ladder, as lift over a neutral audience
  • Rival opening dates, measured as shared audience
What it reads and what you bring

Checked against real audience data

  • Audience fit by listener type, age and city
  • Tour route, as lift for each stop
  • Support acts compared across the route cities
What it reads and what you bring

Checked against real audience data

  • Reader audience by age, genre and place
  • Comp shelf, as reader overlap with comparable titles
  • Adaptation bridge to series, film and podcasts
What it reads and what you bring

Checked against real audience data

  • Listener audience by age and place
  • Topic map, as tags rival shows do not own
  • Shows to swap with and sponsors ranked by listener overlap
What it reads and what you bring

Checked against real audience data

  • Player audience by age and region
  • Fan base bridge to music, series and film audiences
  • Region ranking, as lift over a neutral audience
What it reads and what you bring

Checked against real audience data

  • Audience fit by listener type, age and city
  • Which of your cities the audience is strongest in
  • Support acts compared across the cities
What it reads and what you bring

Questions people ask.

The short answers. The rest are on the how it works page.

How it worksSee the examples
  • Is Oraqul an AI agent or a dashboard?
    An agent. You say what you are working on in plain words, and it decides what to look up, tests what it finds, checks its own draft and comes back with a plan. You keep talking to it in the same chat.
  • Where does the data come from?
    Taste and place come from Qloo, which holds audience taste data across film and TV, music, books, podcasts, games, brands and places. Dated market facts such as rivals and release windows come from web research, each linked to its page. Code computes every number.
  • Can the AI make up a number?
    No. Code works out every score and verdict from the data. The AI only writes the words around them, and an answer that names something outside the data is rejected and rerun.
  • What happens after the launch?
    Add your results as totals by city or age band, with the period and where they came from. Oraqul sets them against the plan and writes a revised plan beside the old one. It says what happened, never why: a cause is a hypothesis to test.
  • Does it forecast sales or streams?
    No. It shows who likes what and where, and gives a direction, not a forecast. When you add your own results, it compares them with what the plan expected.
  • What happens to my data?
    Only public names, places and age bands leave Oraqul. Uploaded results are kept as totals, and your work is visible only to your team.

Start anywhere.
Leave with a plan you can revise.

Create accountSee the examples