Real-Time Creator Royalty Distribution Engine with Sema4.ai & AI SDK
Indonesia is establishing digital networks to connect content creators directly with global commercial markets. Managing multi-jurisdictional royalty distributions requires transparent, micro-payment routing, automated contract parsing, and instant dispute resolution when stream metadata is inconsistent. In this challenge, you will build a full-stack royalty settlement engine using Vercel's AI SDK in TypeScript and Sema4.ai actions for workflow execution. The system parses content usage contracts, verifies global stream metrics, calculates fractional payout structures, and dispatches dynamic payment tasks via Sema4.ai digital workers.
What you are building
The core problem, expected build, and operating context for this challenge.
Develop an automated creator royalty distribution pipeline using Vercel AI SDK and Sema4.ai action orchestration.
How work is evaluated
Evaluates contract extraction precision and accurate payout allocation through Sema4.ai tool tasks.
Challenge datasets
Public datasets, plus the private datasets you have access to.
How submissions are scored
These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.
payout_accuracy
Payout sums must match expected output within 0.01 tolerance.
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
processing_speed_tps
Transactions parsed and executed per second • target: 20 • range: 1-100
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
What you should walk away with
Implement Vercel AI SDK tool calls and streamable structured objects in TypeScript
Construct Sema4.ai action packages for secure, deterministic micro-payout executions
Automate legal license agreement parsing and split-rate extraction
Implement automated discrepancy detection for multi-platform streaming logs
Reference links and supporting material
Dataset of creator licenses, multi-platform stream metrics (YouTube, Spotify, TikTok), and transaction logs.
Challenge setup
Evaluates contract extraction precision and accurate payout allocation through Sema4.ai tool tasks.
Challenge input
JSON containing contract text and platform view counts
AI SDK
Required for structured output generation in TypeScript.
Sema4.ai
Required for secure robot action execution.
Evaluated output
JSON containing payout breakdown per rights holder
- Payout sums must match expected output within 0.01 tolerance.
- Transactions parsed and executed per second • target: 20 • range: 1-100
- Benchmark: TS-Agent-Eval
- Processing Speed Tps target: 20
- 1 public reference case
- JavaScript execution harness
- javascript 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
- Sema4.ai · Required
- Steamship · Optional
- Fiddler AI · Optional
Evaluation contract
- payout_accuracy · Weight 1
- processing_speed_tps · Weight 1
Metrics
- processing_speed_tps · Target 20
Benchmarks
- TS-Agent-Eval
- general
Reference cases
- 1 public reference case
Workflow tasks
- Task 1
Input: JSON containing contract text and platform view counts
Output: JSON containing payout breakdown per rights holder
Execution harness: JavaScript
Evaluation tools
- AI SDK · LLM Orchestration
- Sema4.ai · Agent Automation Platform
Recipe freeze marker
No recipe freeze time is recorded.