A request from Outlook, Trans.eu or TimoCom waits while the sales rep calculates the distance, finds a similar trip in CargoWise and writes up the terms. The assistant prepares a draft quote with a price from your rate sheet and history, and the sales rep adjusts the margin and sends it.
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At a forwarding or transport company, a transport request is often won on speed. A customer sends the same email to several carriers in Outlook, or posts the cargo on the Trans.eu or TimoCom exchange, and takes the quote from whoever replied first and clearly. Meanwhile the sales rep calculates kilometers, checks CargoWise for what you charged for a similar route last month, remembers whether deferred payment terms apply to that customer, and writes the quote from scratch. When there are many requests, some replies go out the next day, and some prices are calculated from memory and differ from company rules.
The assistant receives the request from Outlook or from Trans.eu and TimoCom notifications and extracts the route, cargo parameters, dates and special requirements. From your rate sheet and the distance it calculates a base price, from the trip history in CargoWise or FireTMS it shows similar earlier cargo with their prices and actual cost, and it prepares a draft quote from your template: price, payment term, loading and delivery terms, liability, validity. The sales rep sees the draft in Outlook next to the basis of the calculation, adjusts the margin or terms and sends it from their own mailbox, or enters the price on the exchange themselves. The assistant sends nothing to the customer and submits no offers on the exchange. We deploy it through the ChatGPT API on the OpenAI platform, where your rate sheet and requests are not used for model training; the rate sheet and trip history stay in CargoWise and your Excel files, and we integrate with CargoWise through an API, a file export or an email flow, depending on the version. We agree the calculation logic and the distance source with you before launch.
Four steps from input to a record in your system, with human approval wherever there is risk.
The assistant reads the request from Outlook or from a Trans.eu or TimoCom notification and extracts loading and unloading locations, cargo type, weight, pallets, dates, and temperature or ADR requirements. If essential data is missing, it prepares a short question for the customer, which the sales rep sends.
From the distance and your rate sheet, a base price is calculated with surcharges for ferries, road tolls, waiting time or special transport. From the CargoWise or FireTMS history, similar earlier cargo is shown with their prices and cost, so the sales rep can see how the number fits practice.
The quote is prepared from your template with the price, terms and validity period and delivered to the sales rep as a draft in Outlook. The sales rep reviews it, changes the margin or terms, approves it and sends it from their own mailbox, or enters the price on Trans.eu themselves. The approved price is recorded in the request card in CargoWise.
Unusual cargo, new routes or customers with individual terms are flagged by the assistant so that the sales rep pays more attention. You change the rate sheet and surcharges yourselves in Excel or SharePoint, and we monitor how often sales reps edit the draft and tune the logic.
Your rate tables, surcharge rules and distance source combined into one calculation in Excel or SharePoint that you can change without programming.
A quote form in your style with the price, terms and validity period, prepared as an Outlook draft for review and sending from the sales rep's mailbox.
A search for similar cargo in your CargoWise or FireTMS by route, cargo type and period, through an API or an export, shown next to the calculation with the actual cost.
Monitoring in the first month, analysis of corrections and tuning of the calculation logic based on what sales reps change most often in Trans.eu and Outlook requests.
ChatGPT via API + company rate sheet + trip history from CargoWise or FireTMS + Outlook and Trans.eu requests. We choose the integration method with CargoWise after checking your version. Read more about this service and its limits on the service page.
No. The draft is always reviewed and sent by the sales rep from Outlook, and the price on the Trans.eu or TimoCom exchange is entered by the sales rep. That way you keep control of the margin, special terms and the relationship with the customer, and the assistant only saves calculation and writing time.
Yes. We take the trip history from CargoWise or FireTMS through an API, a file export or an email flow, depending on the version, and the rate sheet can stay in Excel in a SharePoint folder. We choose the integration method after a check at the start of the implementation. What is not in the rate sheet, the assistant does not guess but flags for the sales rep.
We use ChatGPT through the API on the OpenAI platform, where, under the contract terms, the data passed is not used for model training. The rate sheet and CargoWise history are stored in your systems, and only the part needed for the specific request is passed to the model. If you prefer, we can deploy the same solution with Claude through Amazon Bedrock in an EU region.
DKV and Eurowag statements and toll, ferry and subcontractor invoices arrive from Outlook and portals, and an accountant keys them into SAP…
Orders arrive in Outlook with a PDF, from the Trans.eu exchange and from Transporeon, and the dispatcher retypes them into CargoWise by hand.
Drivers send photos of CMR and declarations through Viber or Teams, and logistics checks them by eye and attaches them to the trip in CargoWise by…
Drivers call the dispatcher with the same questions: how to fill in a CMR, what to do after an accident, when loading is.
This service is delivered by specialists with valid international certifications. Their expertise is confirmed by independent organisations, not by us.
AI systems are deployed with protection against data leakage and model abuse.
The AI security programme and its controls are managed following the ISACA methodology.
AI risks are identified and managed like any other IT risk.
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