Sanctions Regime Transition Monitor with LangChain and Modal
Rapid shifts in state terrorism designations require instant dynamic updates to global transaction filtering rules without introducing processing downtime. You will construct a serverless LangGraph streaming pipeline on Modal that evaluates dynamic compliance policies, ensuring zero unmonitored payment transactions during active regulatory transitions.
What you are building
The core problem, expected build, and operating context for this challenge.
Build a serverless dynamic policy update pipeline on Modal using LangChain and LangGraph to process transaction streams through updated regulatory state engines.
How work is evaluated
Evaluates transaction clearance logic before and after dynamic policy update event.
Shared data for this challenge
Review public datasets and any private uploads tied to your build.
How submissions are scored
These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.
policy_switch_precision
Ensures policy switch applies immediately to post-update transactions
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
switch_latency_ms
Time taken to apply new rule engine in pipeline • target: 50 • range: 0-500
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
What you should walk away with
Construct dynamic stateful graphs using LangChain and LangGraph
Deploy serverless, high-concurrency event handlers on Modal runtime
Handle live policy switches during ongoing transaction streaming
Achieve zero transaction processing downtime during compliance rule updates
Reference links and supporting material
Stream of 5,000 cross-border transactions straddling a simulated regulatory status transition event.
How this agent runs
Evaluates transaction clearance logic before and after dynamic policy update event.
Challenge input
JSON containing transaction jurisdiction and timestamp
LangChain
Provides LangGraph state machinery and framework primitives.
Modal
Serverless Python deployment engine for high-concurrency execution.
Evaluated output
JSON with status ('CLEARED'|'BLOCKED') and applied_policy_version
- Ensures policy switch applies immediately to post-update transactions
- Time taken to apply new rule engine in pipeline • target: 50 • range: 0-500
- Benchmark: SanctionSwitch-Eval
- Switch Latency Ms target: 50
- 1 public reference case
- Python execution harness
- Python sandbox (unavailable on Versalist)
View technical recipe
Configured tools
- Modal · Optional
- Langchain · Required
- LangChain · Optional
- Modal · Optional
- Langchain · Required
- LangChain · Optional
Evaluation contract
- policy_switch_precision · Weight 1
- switch_latency_ms · Weight 1
Recipe state
This is a preview. The configuration can change before the evaluation recipe is locked.