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Challenge

Build an ASEAN Creative Economy IP Valuation RAG Pipeline with LlamaIndex

Construct a creative economy intellectual property valuation engine for ASEAN regional trade. Using LlamaIndex, index regional royalty database records and copyright policies to estimate fair market value and calculate cross-border tariff duties on digital creative assets.

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Challenge brief

What you are building

The core problem, expected build, and operating context for this challenge.

Deploy a LlamaIndex RAG system to standardize regional creative economy data and perform intellectual property valuations.

Delivery guide

How work is evaluated

Evaluation

Evaluate IP valuation outputs against standardized ASEAN royalty model standards.

Datasets

Challenge datasets

Public datasets, plus the private datasets you have access to.

Evaluation rubric

How submissions are scored

These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.

Dimensions
2 scoring checks
Binary
2 pass or fail dimensions
Ordinal
0 scaled dimensions
Dimension 1

valuation_range_check

Valuation falls within calculated confidence interval

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Dimension 2

valuation_accuracy

Relative percentage error against benchmark appraisal • target: 0.93 • range: 0-1

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Learning goals

What you should walk away with

  • Build a LlamaIndex vector pipeline over ASEAN creative asset registries

  • Implement standardized schema mappings for diverse regional IP definitions

  • Automate dynamic royalty and fair-market valuation calculations for digital media

  • Output structured compliance reports for ASEAN trade tariff harmonisation

Resources and assets

Reference links and supporting material

Dataset notes

Dataset of regional creative asset licensing agreements and royalty rates across ASEAN economies.

Challenge setup

Evaluate IP valuation outputs against standardized ASEAN royalty model standards.

Challenge input

JSON with asset_category, annual_license_count, avg_royalty_usd, asset_region

LlamaIndex

Enterprise data framework for indexing unstructured trade datasets.

Evaluated output

JSON with estimated_ip_value_usd, confidence_interval, applicable_tariff_rate

Evaluation checks
  • Valuation falls within calculated confidence interval
  • Relative percentage error against benchmark appraisal • target: 0.93 • range: 0-1
Configured evaluation evidence
  • Benchmark: IP_Valuation_Bench
  • Valuation Accuracy target: 0.93
  • 1 public reference case
Configured runtime
  • Python execution harness
  • Python sandbox (unavailable on Versalist)

Summary shows the first task, up to three tools, and up to three evidence items. Open the technical recipe to view all configured items.

View technical recipe

Configured tools

Action Space
  • Llama Index · Required
  • CrewAI · Optional
Policy Serving
  • OpenRouter · Optional
Orchestration
  • OpenRouter · Optional

Evaluation contract

  • valuation_range_check · Weight 1
  • valuation_accuracy · Weight 1

Metrics

  • valuation_accuracy · Target 0.93

Benchmarks

  • IP_Valuation_Bench
  • general

Reference cases

  • 1 public reference case

Workflow tasks

  1. Task 1

    Input: JSON with asset_category, annual_license_count, avg_royalty_usd, asset_region

    Output: JSON with estimated_ip_value_usd, confidence_interval, applicable_tariff_rate

    Execution harness: Python

Evaluation tools

  • LlamaIndex · RAG Framework

Recipe freeze marker

No recipe freeze time is recorded.

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