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Challenge

Build a COSMIC AML Risk Intelligence Agent with Vercel AI SDK and Galileo

Construct an automated Anti-Money Laundering (AML) risk scoring and intelligence agent to analyze cross-institutional transaction logs using Vercel AI SDK and Galileo. Implement real-time suspicious activity reporting with zero regulatory leakage.

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Challenge brief

What you are building

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

Orchestrate multi-bank transaction graph inspection using Vercel AI SDK tools integrated with Galileo evaluation guardrails for MAS COSMIC compliance.

Delivery guide

How work is evaluated

Evaluation

Evaluates the agent's ability to identify transaction laundering rings, enforce guardrails via Galileo, and produce accurate STR reports.

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

schema_conformance

Ensures output JSON matches target regulatory schema

Binary check

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

Dimension 2

precision

Precision of laundering ring identification • target: 0.95 • 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

  • Master building streaming agent workflows using Vercel AI SDK tool calling

  • Integrate Galileo for continuous hallucination monitoring and guardrail telemetry

  • Implement graph analytics algorithms to detect cross-institutional money laundering rings

  • Synthesize MAS-compliant Suspicious Transaction Report (STR) summaries with verifiable provenance

Resources and assets

Reference links and supporting material

Dataset notes

Synthetic multi-bank ledger containing layered transactions across DBS, OCBC, and UOB mock accounts.

Challenge setup

Evaluates the agent's ability to identify transaction laundering rings, enforce guardrails via Galileo, and produce accurate STR reports.

Challenge input

JSON array of cross-bank transaction logs and account profile data

AI SDK

Provides TypeScript tool streaming and structured output generation.

Galileo

Evaluates hallucination and risk output in real time.

Evaluated output

JSON object with risk_score, laundering_ring_detected (boolean), and structured str_report

Evaluation checks
  • Ensures output JSON matches target regulatory schema
  • Precision of laundering ring identification • target: 0.95 • range: 0-1
Configured evaluation evidence
  • Benchmark: Financial Crime Detection Benchmark (FinCrimeBench)
  • Precision target: 0.95
  • 1 public reference case
Configured runtime
  • 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.

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Configured tools

Action Space
  • Vercel AI SDK · Optional
  • Claude Code · Optional
Observation
  • Galileo · Required
  • Claude Code · Optional
Reward / Eval
  • Galileo · Required
Orchestration
  • Vercel AI SDK · Optional

Evaluation contract

  • schema_conformance · Weight 1
  • precision · Weight 1

Metrics

  • precision · Target 0.95

Benchmarks

  • Financial Crime Detection Benchmark (FinCrimeBench)
  • security

Reference cases

  • 1 public reference case

Workflow tasks

  1. Task 1

    Input: JSON array of cross-bank transaction logs and account profile data

    Output: JSON object with risk_score, laundering_ring_detected (boolean), and structured str_report

    Execution harness: JavaScript

Evaluation tools

  • AI SDK · Agent Orchestration Framework
  • Galileo · AI Guardrail & Telemetry System

Recipe freeze marker

No recipe freeze time is recorded.

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