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Multi-Agent Sanctions Compliance Tracker using CrewAI and Fireworks AI

Rapid shifts in international sanctions lists require immediate reconfiguration of transaction screening parameters for global payment networks. Build a multi-agent compliance squad with CrewAI and Fireworks AI inference to ingest regulatory updates, re-index sanction tables, and evaluate suspended transactions. Achieve 100% detection of sanctioned entities with zero latency degradation on cleared routes.

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What you are building

Orchestrate a crew of specialized compliance agents using CrewAI and Fireworks AI to continuously ingest regulatory updates and screen pending payments.

How work is evaluated

Evaluation

Tests crew efficiency in updating sanction policies and correctly updating transaction release/block decisions.

Datasets

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

How submissions are scored

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

policy_update_test

Ensures status switches to RELEASED upon lifting of sanctions

Binary check

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

Dimension 2

sanction_accuracy

Accuracy of transaction status determinations after regulatory changes • target: 1 • 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

  • Define specialized CrewAI roles: Regulatory Crawler, Rule Reindexer, and Payment Evaluator

  • Configure Fireworks AI high-speed inference endpoints for agent task execution

  • Implement multi-agent sequential and hierarchical task delegation patterns

  • Demonstrate live dynamic update of payment routing decisions following sanction status changes

Resources

Dataset notes

Dataset of 20 regulatory bulletin announcements and 300 cross-border pending transactions in sanction-transition zones.

Challenge setup

Tests crew efficiency in updating sanction policies and correctly updating transaction release/block decisions.

Challenge input

JSON containing news text regarding sanction modification and held transaction queue

CrewAI

Agent collaboration framework

Fireworks AI

Fast model inference runner

Evaluated output

JSON array of transaction IDs with updated statuses (RELEASED or BLOCKED)

Evaluation checks
  • Ensures status switches to RELEASED upon lifting of sanctions
  • Accuracy of transaction status determinations after regulatory changes • target: 1 • range: 0-1
Configured evaluation evidence
  • Benchmark: Sanctions-Eval
  • Sanction Accuracy target: 1
  • 1 public reference case
Configured runtime
  • Python execution harness
  • Python sandbox (unavailable on Versalist)

Shows the first task, up to three tools, and up to three evidence items.

View technical recipe

Configured tools

Action Space
  • CrewAI · Required
  • crewAI · Optional
Policy Serving
  • Fireworks AI · Optional
Training Infra
  • Fireworks AI · Optional

Evaluation contract

  • policy_update_test · Weight 1
  • sanction_accuracy · Weight 1

Metrics

  • sanction_accuracy · Target 1

Benchmarks

  • Sanctions-Eval
  • security

Reference cases

  • 1 public reference case

Workflow tasks

  1. Task 1

    Input: JSON containing news text regarding sanction modification and held transaction queue

    Output: JSON array of transaction IDs with updated statuses (RELEASED or BLOCKED)

    Execution harness: Python

Evaluation tools

  • CrewAI · Multi-Agent Framework
  • Fireworks AI · Inference Engine

Recipe freeze marker

No recipe freeze time is recorded.

Frequently Asked Questions about Multi-Agent Sanctions Compliance Tracker using CrewAI and Fireworks AI