CLIP™
CLIP™ · Workshop

Workshop Answers

Digitizing media & entertainment licensing — what success looks like, how we get there, and what remains to be solved.

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Industry Context — Media & Entertainment

CLIP™ targets the media and entertainment licensing industry — studios, distributors, and content owners who license movies and TV shows to broadcasters, streamers, and pay-TV operators globally.

The Analog World (Today) 📄 Paper Contracts 80–200 pg PDFs, legalese 📊 Spreadsheet Planning Manual rules, formulas 🧠 Tribal Knowledge Planner expertise, not data 🔌 Disconnected Systems RMS, ERP, SF, BI silos Result: 15% revenue leakage Slow, error-prone, reactive → CLIP™ Digitizes The Digital World (CLIP™) 🤖 AI Rule Extraction PDF → JSON in minutes ⚡ Real-time Engine 12K titles in <2s 📈 Intelligent Insights MKE playbooks, forecasts 🔗 Connected Platform ERP + SF + BI + RMS Result: Revenue certainty Fast, accurate, proactive

The digitization opportunity: The M&E licensing workflow is one of the last major media processes still running on paper, spreadsheets, and tribal knowledge. CLIP™ digitizes this end-to-end — from contract ingestion to revenue booking.

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Customer User Persona & Day-to-Day Challenges

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Sales Planner
Primary Persona

Role: Plans and executes licensing deals at Aurora Studios Television / Film Distribution. Decides which movies to sell, to whom, at what price, and when.

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Deal Manager / Finance
Secondary

Revenue recognition, fee reconciliation, cap tracking. Needs auditable verdicts and ERP-ready data.

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VP / Executive
Secondary

Pipeline visibility across all deals. Portfolio-level dashboards for locked, forecasted, and actionable revenue.

A sales planner manages 5–15 active contracts simultaneously, each covering multiple territories, product categories, and 3–5 term years. Every quarter they: re-read contracts, match titles against rules, confirm rights across 6 dimensions (title × territory × language × media type × license × window), calculate fees, and explore near-miss titles ad-hoc.

Core pain: 80+ page contracts read manually, spreadsheet-based planning, 6-dimensional rights checked across disconnected systems, 15% revenue leakage from missed eligible titles, and zero systematic tooling for Make-It-Eligible exploration.
1

What does success mean for you in this project?

Success means delivering a platform that converts contract complexity into revenue certainty:

  • Full workflow automation: Rule extraction → title matching → rights confirmation → fee calculation → revenue booking — in one pipeline.
  • Multi-dimensional coverage: Every title × territory × language × media type × license type × window evaluated. No combination missed.
  • Proactive revenue creation: Systematically identifying titles that could be eligible with targeted actions (boost BO, shift dates, push to another term).
  • Real-time, not quarterly: Every catalog change triggers re-evaluation automatically.
  • 94%+ accuracy on extraction; 15% revenue recovered; minutes not weeks.
The ultimate measure: a sales planner says "I can't do my job without CLIP."
2

What has been your contribution towards this success so far?

  • Architecture Design: Two-engine architecture with bounded contexts, data contracts, and closed intelligence loop.
  • Technical Documentation: TRDs covering system architecture, resource plans, architect's blueprint.
  • Attribute System: Full framework across Qualifiers, Start Dates, Caps, Rate Cards — including Nordic earliest-of rules, territory-language data, tiered pricing.
  • Module 2 PoC: Working proof-of-concept (this app!) demonstrating end-to-end rule evaluation and eligibility bucketing.
  • Investor Artifacts: Roadmaps, executive decks, worked examples (Frontier Quest case study).
  • Knowledge Capture: Structured markdowns for each attribute type, ensuring institutional knowledge persists.
3

What would be a valuable MVP?

A single-contract, end-to-end pipeline proving the closed loop:

  • Module 1: Upload 1 real contract → extract all 4 segments → output rules.json with confidence → 5-step review wizard.
  • Module 2: Rules + ~500 titles → deterministic evaluator → eligibility verdicts → visual timeline with 4 buckets.
  • The "wow": One near-miss title with a concrete lever ("push Frontier Quest screens 3,800 → 4,000 → eligible in T1").
Scope: 1 contract, 4 categories, 4 term years, ~500 titles. No SF/ERP yet. No amendments. Core intelligence loop only. ≤8 weeks.
4

Delivery Flow

4.1 — What is the project?

CLIP™ — AI platform that transforms licensing contracts into structured rules, then identifies which movies are eligible to sell, for how much, and when.

4.2 — Who is the customer?

Primary: Sales Planners at entertainment studios. Secondary: Deal managers, finance, executives.

Pain: Weeks interpreting contracts, spreadsheet cross-referencing, ~15% revenue leakage.

4.3 — How will this help them?

  • 2–3 weeks → minutes
  • Every title × category × term evaluated
  • Make-It-Eligible playbook (not just reporting)
  • Deterministic, auditable verdicts
  • 15% revenue recovered + new revenue created

4.4 — End-to-end flow

  1. Contract arrives — 80-page PDF between Aurora and a broadcaster.
  2. CLIP reads it — Engine 1 extracts rules (qualifiers, dates, caps, rates).
  3. Planner reviews — 5-step wizard; 94%+ correct out of the box.
  4. CLIP matches — Engine 2 evaluates 12K titles in <2s.
  5. Dashboard lights up — "Frontier Quest eligible T1 @ $2.75M", "Bullet Train one lever away."
  6. Revenue flows — Book eligible, queue forecast, act on MKE recommendations.
One sentence: CLIP turns paper contracts into a live revenue radar.
5

3 Open Questions

  • 1. Rights integration in Phase 1?

    Do we need a read-only rights check (Rightsline/FilmTrack) in MVP to avoid false-positive eligibility, or defer to Phase 2?

  • 2. Amendment handling?

    Is MVP scoped to one clean contract version, or must we handle at least one amendment layer from day one?

  • 3. Ground-truth validation?

    Who owns the "golden set" of manually-extracted rules for benchmarking Engine 1's accuracy? How many annotated contracts do we need?