Agent Name
RecallScope Agent
What It Does
RecallScope is an operational recall-response agent for grocery distributors and retailers. It turns public FDA food recall data plus internal supply-chain context into an explainable incident command board and store-level pull sheet.
The agent helps answer:
- What products should we pull or hold?
- Which stores are affected?
- Which suppliers are involved?
- Which customer segments may be exposed?
- What graph evidence supports each action?
Dataset And Why A Graph Fits
RecallScope uses public openFDA food enforcement recall data combined with a realistic synthetic distributor dataset containing SKUs, suppliers, stores, inventory, orders, and customer segments.
A graph fits because recall response is a relationship problem. The important question is not just “what was recalled?” It is “which recalled products match internal SKUs, where are those SKUs stocked, who supplied them, and which customers may be affected?”
Neo4j lets the agent trace paths like:
FDA Recall → Internal SKU → Store Inventory → Supplier → Customer Segment → Action Plan
Aura Agent Tools Used
- Cypher Template tools for incident summaries, pull sheets, action ranking, supplier exposure, and evidence tracing
- Text2Cypher for ad hoc operational questions
- Vector indexes generated for future semantic SKU matching
Demo / Screenshots
Attached:
- Screenshot of the RecallScope Agent in Aura
- Screenshot of the agent producing an incident command board and pull sheet
- Screenshot of the Aura dashboard
- Screenshot of the recall impact graph path
- Short demo video: https://youtu.be/UB2WjVefupc
Notes
The current prototype refreshes openFDA recall data through ingestion scripts and merges it into Neo4j. Internal distributor data is synthetic for the hackathon demo.
