In manufacturing and logistics, every outbound load is a revenue transaction and represents your commitment towards the customers.
When crates are miscounted at dispatch, loads go out short, customers raise disputes, and the cost of recovery far exceeds what a structured dispatch management system would have prevented.
Manual counting is inconsistent, as you might have experienced in the past, and there is no real-time mechanism to match physical loads against sales order requirements before a truck leaves the facility.
DynaTech's Dispatch Crate Management AI Agent brings computer vision capabilities, automating the entire workflow, including consistent detection, virtual counting line, real-time order validation, and proof-of-loading at the exact point of dispatch.
Microsoft Copilot is a GenAI-enabled productivity assistant, and your teams can use it to;
CoPilot is not designed to monitor a moving dispatch belt, detect and count physical objects in real time, or cross-reference a live camera feed against a sales order record in Dynamics 365.
DynaTech's Dispatch Crate Management AI Agent is purpose-built for physical dispatch validation. It applies computer vision at the detection layer, where every crate is counted as per the movement, connects to Dynamics 365 through configured API and integration layers, and surfaces structured discrepancy alerts at the precise point of loading.
Using Azure AI Vision combined with YOLO-based object detection, the agent automatically identifies and counts crates as they move through the dispatch belt, increasing the count when it moves forward and decreasing the count when it moves backward.
The detection layer processes live camera feeds to deliver accurate, consistent counts regardless of dispatch volume, belt speed, or shift.
Detected crate counts are automatically cross-referenced by the dispatch automation solution against sales orders, which the tool fetches from Dynamics 365 APIs and configured integration layers, and validates whether the dispatched quantity matches what the order requires.
Our crate management system AI agent sends an alert in case of discrepancies, while mentioning the order context and the discrepancy detail immediately. Among many use cases of computer vision, our agent helps your teams with enough time to correct the dispatch order before the truck departs. This is real-time discrepancy detection applied at the last point where intervention is possible.
Every validated dispatch generates a timestamped, structured proof-of-loading record linked to the corresponding sales order. This means you will have an auditable evidence trail of all the crates and loads dispatched, and this helps with compliance, dispute resolution, and operational documentation.
By surfacing count mismatches at the loading stage, the agent functions as a systematic barrier against lost crates and incorrect shipments. Operational losses that accumulate quietly over time, through recurring short-shipments, unresolved disputes, and undetected errors, are identified and preventable at the source.
In high-volume dispatch environments, the gap between what is physically loaded and what the sales order requires often goes undetected until a customer dispute or a reconciliation cycle flags the discrepancy.
For enterprise-scale warehouses and units sending out thousands of crates every day, manual counting is unreliable at scale, and most of them don’t have a proper dispatch management system software. Even the ones with the right system rely on manual processes; as a result, lost crates and short shipments become recurring operational and financial losses with no early warning system in place.
DynaTech's automated dispatching solution and computer vision AI use cases address this at the source, at the dispatch belt, before the load is sealed and before the truck leaves.
DynaTech's Dispatch Crate Management AI Agent operates at the dispatch belt, using computer vision to detect and count crates as they move through the loading zone.
Those counts are validated against sales order data accessed through Dynamics 365 API integration layers in real time. When the count aligns with the order, a proof-of-loading record is generated automatically.
When it does not, a discrepancy alert is sent with order context and count details, escalating the matter with the right person or team to ensure they can fix it. The agent reads and validates against configured data through secure API access; it does not modify the ERP schema or write to core data structures during operation.
A manufacturing facility dispatches hundreds of crates across multiple shifts daily. Supervisors rely on manual counts, and short shipments are only discovered during customer complaints days later.
With DynaTech's agent in place, the computer vision layer counts every crate on the dispatch belt autonomously and cross-references the total against the active sales order in Dynamics 365. A count shortfall is detected and flagged before the load is sealed, giving the team time to correct the dispatch before it leaves the facility.
With manually driven processes, dispatch accuracy varies significantly across shifts, especially in a high-volume warehouse. Issues like manual counting errors, typo errors, and others can cause delays in loading due to inconsistent manual counting.
DynaTech's AI agent applies the same detection and validation logic to every load, every shift, without variability, and from this, the managers gain a consistent, reportable accuracy baseline across all dispatch activity through the Power BI reporting layer.
| Business Challenge | Agentic AI Solution |
| Crates are miscounted or missed during high-volume shifts, resulting in discrepancies in shipments that surface only after customer delivery. | The AI agent counts crates automatically at the dispatch belt using computer vision, highlighting count mismatches before the load is sealed and dispatched. |
| Manual sales order verification is slow and inconsistent when teams are managing multiple outbound loads simultaneously across shifts. | Sales order validation runs automatically through Dynamics 365 API integration, comparing detected counts against order quantities in real time without requiring manual lookup. |
| There is no structured proof-of-loading documentation, leaving the business exposed in customer dispute scenarios with no auditable evidence. | Every validated dispatch generates a timestamped, structured proof-of-loading record linked to the corresponding sales order, creating a documented evidence trail automatically. |
| Manual teams cannot work 24/7, lowering productivity, and even if they manage to work around the clock, fatigue is natural. | The smart AI-detection systems run 24/7 without fatigue and errors, ensuring your loads are not compromised. |
DynaTech's Dispatch Crate Management AI Agent operates across clearly separated layers.
DynaTech’s deployment team works on;
DynaTech's Dispatch Crate Management AI Agent is deployed without modifying your core Dynamics 365 ERP schema.
Deployment covers;
Our team configures the automated dispatch logistics agent to align with your sales order structure and dispatch workflow. Connect with DynaTech's team directly for a deployment assessment specific to your environment.
Dispatch errors, lost crates, and short-shipment disputes carry real financial and operational costs that compound over time. With DynaTech's Dispatch Crate Management AI Agent, count accuracy improves at the source, manual verification effort drops, and every outbound load carries a validated proof-of-loading record. Fewer disputes. Faster resolution. Tighter dispatch operations from day one.