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Challenge

LlamaIndex & Galileo ONDC Merchant Inventory Risk Agent

Mitigate regional inventory stockout risks for quick-commerce catalog integrations across Open Network for Digital Commerce (ONDC). You will construct an agentic index that evaluates supplier health, demand signals, and supply disruption risks to trigger automated reorder workflows.

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Challenge brief

What you are building

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

Build a LlamaIndex agentic workflow using Galileo hallucination monitoring to analyze ONDC merchant inventory feeds and dynamically optimize fulfillment routing.

Delivery guide

How work is evaluated

Evaluation

Evaluates the agent's ability to process catalog updates and generate accurate, un-hallucinated reorder actions.

Datasets

Shared data for this challenge

Review public datasets and any private uploads tied to your build.

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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 Validation Test

Ensures output conforms to reorder action JSON schema

Binary check

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

Dimension 2

Reorder Precision

Accuracy of trigger thresholds based on stockout math • target: 0.95 • range: 0.85-1

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

  • Implement LlamaIndex agentic routing for dynamic multi-catalog ingestion

  • Integrate Galileo AI telemetry for monitoring hallucination rates in inventory recommendations

  • Construct a consent-aware supplier risk assessment pipeline for ONDC protocols

  • Automate reorder threshold triggers based on predicted regional demand spikes

Resources and assets

Reference links and supporting material

Dataset notes

Simulated ONDC grocery catalog feed with fluctuating stock levels and delivery lead times across multiple regional hubs.

How this agent runs

Evaluates the agent's ability to process catalog updates and generate accurate, un-hallucinated reorder actions.

Challenge input

JSON containing store inventory feeds and supplier lead times

LlamaIndex

Provides data indexing and agentic routing tools.

Galileo

Monitors hallucination and agent tool accuracy.

Evaluated output

JSON array of reorder actions with confidence and urgency flags

Checks for
  • Ensures output conforms to reorder action JSON schema
  • Accuracy of trigger thresholds based on stockout math • target: 0.95 • range: 0.85-1
Proof of success
  • Benchmark: SupplyChainAgent-Bench
  • Reorder Precision target: 0.95
  • 1 public reference case
Runtime evidence
  • Python execution harness
  • Python sandbox
View technical recipe

Configured tools

Action Space
  • Llama Index · Optional
  • Hamming · Optional
Observation
  • Galileo · Required
Reward / Eval
  • Galileo · Required

Evaluation contract

  • Schema Validation Test · Weight 1
  • Reorder Precision · Weight 1

Recipe state

This is a preview. The configuration can change before the evaluation recipe is locked.

Frequently Asked Questions about LlamaIndex & Galileo ONDC Merchant Inventory Risk Agent