Supply Chain Supply Chain Operations
Use Case

Proof of Delivery Data Extraction and Reconciliation

An AI agent that automates the processing of Proof of Delivery (POD) documents received from carriers. It extracts key data, matches it against shipment records, identifies any delivery exceptions noted on the document (like damages or shortages), and archives the clean PODs while flagging exceptions for immediate human attention.

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Process Details

Inputs

Proof of Delivery documents (PDF, JPG, PNG) Shipment data (tracking numbers, order details)

Outputs

Digitized and archived Proof of Delivery records. Automated confirmation of successful deliveries. Immediate alerts and cases created for delivery exceptions (damages, shortages)

Systems

ERP System / Transportation Management System (TMS) - for shipment data

The Challenge

Manual processes
create real problems.

  1. 1

    High potential for costly errors from manual data handling.

  2. 2

    Significant time and resources are spent on repetitive, low-value work.

  3. 3

    The manual process is difficult to scale without increasing headcount.

  4. 4

    Process bottlenecks lead to delays and missed deadlines.

The Solution

Describe it in English.
It runs deterministically.

  1. 1

    POD Ingestion

    The AI agent monitors Email Inboxes and Carrier Portals for incoming POD documents, which are typically PDFs or image files.

  2. 2

    Data Extraction

    The agent reads the POD and extracts key data points: the tracking or PRO number, the date and time of delivery, the name of the signatory, and crucially, it scans the document for any handwritten notes, checked boxes, or typed comments indicating an exception.

  3. 3

    Shipment Record Matching

    The extracted tracking/PRO number is used to look up the corresponding shipment record in the company's ERP System or Transportation Management System (TMS) to confirm the consignee and expected delivery date.

  4. 4

    Exception Analysis

    If any notes or checked boxes are detected, the agent interprets the meaning (e.g., "carton crushed," "short 2 cases," "refused") and categorize the exception.

  5. 5

    Automated Routing Based on Outcome:

    Clean PODs: If the POD is signed, dated, and has no exceptions, the agent automatically links it to the shipment record in the ERP System and flags the order as "Delivered." PODs with Exceptions: If an exception is found, the agent creates a case, attaches the POD and a summary of the issue, and routes it via Email to the appropriate team (e.g., Claims department for damage, Customer Service for shortages).

Primary Benefits

What you gain with
Kognitos automation.

Increase Efficiency

Dramatically reduce the time and manual effort required to complete the process.

Enhance Accuracy

Eliminate human error to ensure data integrity and reduce financial risk.

Empower Employees

Free your team from monotonous tasks, allowing them to focus on strategic work that requires their expertise.

Improve Scalability

Handle growing volumes of work without a proportional increase in operational costs.

Ensure Transparency

Maintain a complete, auditable trail of every action the AI agent takes, described in plain English.

Challenges

Solution

This use case solution follows these general steps at a high level:

  1. POD IngestionThe AI agent monitors Email Inboxes and Carrier Portals for incoming POD documents, which are typically PDFs or image files.
  2. Data ExtractionThe agent reads the POD and extracts key data points: the tracking or PRO number, the date and time of delivery, the name of the signatory, and crucially, it scans the document for any handwritten notes, checked boxes, or typed comments indicating an exception.
  3. Shipment Record MatchingThe extracted tracking/PRO number is used to look up the corresponding shipment record in the company's ERP System or Transportation Management System (TMS) to confirm the consignee and expected delivery date.
  4. Exception AnalysisIf any notes or checked boxes are detected, the agent interprets the meaning (e.g., "carton crushed," "short 2 cases," "refused") and categorize the exception.
  5. Automated Routing Based on Outcome:Clean PODs: If the POD is signed, dated, and has no exceptions, the agent automatically links it to the shipment record in the ERP System and flags the order as "Delivered." PODs with Exceptions: If an exception is found, the agent creates a case, attaches the POD and a summary of the issue, and routes it via Email to the appropriate team (e.g., Claims department for damage, Customer Service for shortages).

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