Working Principle
ParcelAI leverages the integration of Streamlit, Snowflake, and ChatGPT to provide a seamless and intuitive data querying experience. Users can easily access and understand complex logistics data through natural language queries, ensuring efficient and informed decision-making in their logistics operations.
We will gradually enrich our data model of ParcelAI according to your feedback.
Here's a simple representation of the current table and each column's descriptions. You can ask the question related to any of the data fields available at the moment:
- Table 1. Shipment Table:
- CUSTOMER_NAME: The name of the customer.
- ACCOUNT_ID: The account id of the shop.
- DESTINATION_COUNTRY: The ISO code of the destination country.
- TRACKING_CODE: The tracking code of the shipment.
- SHOP_ORDER_ID: The order id of the shop.
- DESTINATION_ZIP_CODE: The Zip code of the destination.
- PLANNED_PICKUP_DATE: The planned date for pickup of the shipment.
- SHIPMENT_ID: Internal 7S id of the shipment.
- CARRIER_NAME: The name of the carrier.
- SHOP_NAME: The name of the shop.
- DESTINATION_CITY: The city of the destination.
- CREATED_AT: The creation date of the shipment.
- IS_RETURN_PARCEL: Indicates if the parcel is a return parcel. 'Yes' means it is a return parcel and 'No' means it is an Outbound parcel.
- Table 2. Events Table:
- EVENT: The event related to the shipment.
- EVENT_TIME: The time of the event.
- SHIPMENT_ID: Internal 7S id of the shipment (used to join to datamodel tables).
- ACCOUNT_ID: The account id of the shop.
- Table 3. Status Table:
- STATUS: The status of the shipment.
- STATUS_TIME: The time of the status.
- SHIPMENT_ID: Internal 7S id of the shipment (used to join to datamodel tables).
- ACCOUNT_ID: The account id of the shop.
The data columns are joined between all the tables by some common references (SHIPMENT ID). ParcelAI detects it automatically and looks for the answers across all the tables to give you the most precise answers!
The information might vary depending on the provided context. If you want to know more detailed information about any specific column or table, feel free to ask ParcelAI directly!
Use Cases
The current version of ParcelAI will allow you to
- Real-time Order Tracking. Get up-to-the-minute updates on the event and status of your shipments. The chatbot can provide detailed information on each shipment, ensuring you stay informed about your logistics processes. ParcelAI can also explain the meaning of each event, when, how and why each event triggered.
- Volume and KPIs Questions. Access basic information about your performance quickly and easily. The chatbot enables instant calculations of key performance indicators such as Damage Rate, Returns Rate, Delivery Success Rate, Volumes, and First Hub Scan Rate. These insights will help you make data-driven decisions to improve your logistics operations. ParcelAI can also compute generic Lead Times calculations (days difference between Creation and First Delivery Attempt) - however, no holidays and carrier-specific working days will be taken into account at this version of Parcel