Wahyd Logistics has integrated Agentic AI into LocomotePro, its transport and fleet management platform, adding an assistant that handles customer conversations by text and voice, works in four languages, and hands off to a human when the situation calls for it.
Most logistics software still treats support as a ticket form and a help center nobody reads. LocomotePro's approach is different in one important way: the AI is not a chatbot bolted onto the website. It is an agent with a defined job, a knowledge base built from the product itself, and a clear line of escalation when it reaches the edge of what it should decide on its own.
Two assistants, two jobs
The integration is actually two agents, each with a narrow remit.
The first is a customer-facing sales and support agent, available on the LocomotePro website and inside the app. It opens with a short intake, then lets the visitor choose between chat and a call. The call option is built to feel like a real phone call: ringing, a spoken language menu, then a live voice conversation with captions on screen. Logged-in customers get more: an account view, a live fleet snapshot, answers specific to their own vehicles and trips, and a priority handoff to a named account manager.
The second is a "how do I use the system" helper for people already inside the portal. It is deliberately simpler. A dispatcher types or speaks a question, gets an answer in English or Bangla, and can have it read aloud. There is no call flow, no login, no sales layer. It exists to cut the time between "I don't know where this is" and "found it."
Keeping the two separate is a design choice. A sales agent that also tries to teach you the trip status workflow ends up doing neither job well.
Grounded in the product, not the internet
What separates an agent from a generic AI chat window is what it is allowed to know. Both LocomotePro assistants are grounded in the platform's own modules: entities, trips, financials, fleet tracking, maintenance, geofences, and reporting. The help assistant draws on a structured knowledge base of over 120 how-to articles, maintained in parallel English and Bangla versions, with answer rules specific to the Bangladesh market.
That grounding is why the assistant can walk a user through creating a trip from a rate confirmation, assigning a driver, or reading a fuel-efficiency report, rather than producing a confident answer about a feature that does not exist. Updating what the assistant says is a matter of editing the knowledge base, not rewriting code.
Voice built for the markets LocomotePro serves
Language coverage is where the integration reflects Wahyd's footprint. The customer agent speaks English, Urdu, Arabic, and Bangla, with right-to-left support where needed, and the voice channel uses dedicated neural voices per language rather than a single accented default. For fleet operators in Dhaka, Karachi, Riyadh, or Dubai, that is the difference between a tool their staff will use and one they will route around.
Escalation as a feature
The part of the design that will matter most to operators is the escalation ladder. The agent resolves what it can, routes the rest to a specialist, and on the customer side can put a logged-in user through to their account manager or a helpline call. The AI is not positioned as a replacement for support staff. It is positioned as the first layer, so human time goes to the problems that need it.
This is consistent with how Wahyd has described its broader Logistics Operating System: systems built from problems in its own operations and tested in real work before they are sold. The support agent follows the same pattern. It handles the repetitive layer of questions Wahyd's own teams were already answering by hand.
Source: MEA Tech Watch Press Reporter
