Build an E2E Payment Rail Recovery RAG Agent with LlamaIndex
Payment failures across complex end-to-end routing networks require instant root-cause analysis and mitigation strategies. Develop an enterprise knowledge and recovery RAG agent using LlamaIndex that indexes error logs and dynamically suggests routing repairs.
What you are building
Build an enterprise payment operations agent using LlamaIndex with dynamic query engines to diagnose payment routing failure logs.
How work is evaluated
Evaluates accuracy of error diagnosis and correctness of reroute action recommendations.
Datasets
Public datasets, plus the private datasets you have access to.
How submissions are scored
test_no_retry_closed_account
Ensure closed account code prevents useless automated retry
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
diagnosis_accuracy
Accuracy of root cause diagnosis • target: 0.96 • range: 0.88-1
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
Learning goals
Index ISO 20022 error codes and acquirer specification documentation using LlamaIndex.
Create dynamic agent query engines to diagnose transactional error trajectories.
Deliver sub-second root cause diagnosis and automated rerun actions.
Resources
Synthetic payment failure logs with ISO 20022 rejection codes and gateway technical guides.
Challenge setup
Evaluates accuracy of error diagnosis and correctness of reroute action recommendations.
Challenge input
JSON payment reject message containing raw status code and acquiring bank response
LlamaIndex
Framework requirement
Evaluated output
JSON containing root_cause, recovery_action, retry_recommended
- Ensure closed account code prevents useless automated retry
- Accuracy of root cause diagnosis • target: 0.96 • range: 0.88-1
- Benchmark: RAG Diagnostics Benchmark v1
- Diagnosis Accuracy target: 0.96
- 1 public reference case
- 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
- Llama Index · Required
- LlamaIndex · Optional
- Llama 3.2 · Optional
Evaluation contract
- test_no_retry_closed_account · Weight 1
- diagnosis_accuracy · Weight 1
Metrics
- diagnosis_accuracy · Target 0.96
Benchmarks
- RAG Diagnostics Benchmark v1
- general
Reference cases
- 1 public reference case
Workflow tasks
- Task 1
Input: JSON payment reject message containing raw status code and acquiring bank response
Output: JSON containing root_cause, recovery_action, retry_recommended
Execution harness: Python
Evaluation tools
- LlamaIndex · agent_framework
Recipe freeze marker
No recipe freeze time is recorded.