PROPOSED AI APPLICATION

Screening promotion drafter

Promotional copy takes too long

Cinema and screening operatorsKnowledge and workflow pilotProposed solution scope

The problem and the proposed outcome

Application: Cinema and screening operators — Screening promotion drafter
Problem to solve: Promotional copy takes too long
Target buyer: Cinema managers, screening clubs
Intended use: Employee / expert own workflow; internal business solution
Benefit to test: Test whether approved drafts require less preparation effort at the required factual standard.
Potential delivery: Internal application, reviewer dashboard, private assistant or authorized user portal; choose one surface after validating the workflow.

AI method: Language drafting and summarization
Method code: L
AI contribution: Use a language model to organize permitted facts into a requested draft or summary; link facts to inputs and flag unknown details.
Output artifact: Editable draft or summary grounded in supplied facts.
Core modules: Approved facts / brief → draft generation → factual checks → human approval
Simple baseline: Reusable text templates, manual writing and rule-based mail merge.
Why test AI: Could help when language and structure vary between cases; template filling remains a useful lower-complexity baseline.

Pilot track: Knowledge and workflow pilot
Required data: Licensed film metadata; approved venue offers
Data readiness: Verified source facts, content rights, an approved template and examples of acceptable drafts are needed.
First development step: Gather permitted source-to-approved-draft examples and establish a factual review rubric.
Initial MVP scope: One defined task, one permitted dataset and one reviewer workflow. Manual upload or authorized export first; no unattended external action. Validate the model before live integration.
Demo data: Synthetic or licensed public samples may illustrate the workflow. Real benefit and model performance need representative authorized held-out data.
Buyer validation question: Ask Cinema managers, screening clubs: show a recent case where promotional copy takes too long, record the present effort or error, and confirm whether the required data can lawfully be used.

Primary success metric: Approved content preparation time
Model evaluation: Assess factual consistency, completeness, unsupported statements, reviewer edits and approved preparation time.
Metric target: Set after baseline measurement; no improvement or accuracy result asserted.

Specialist review: No special flag; domain review still applies
Human review boundary: Authorized user reviews critical facts, output quality and access before publishing, importing or acting.
Domain review: Confirm data ownership, access, source rights, reviewer authority and correction routes with the operator.
Related micro-ERP catalogue IDs: IWA-B-D39D9D60C711; IWA-B-640635CF0C2D; IWA-B-A8DE080542E8
Integration status: Potential segment link only; no product integration implemented.