Qatar Open Innovation

Challenge Statement

The Future of Operational Visibility: Creating an Intelligent, Multi-Channel "Air-Traffic-Control" Layer for Logistics

How might we create an AI communications co-pilot for logistics operations by triaging, clarifying and escalating time-critical messages across communication channels?

GWC is seeking solution providers to develop an intelligent "air-traffic-control" layer , a unified communications co-pilot that sits on top of existing channels rather than replacing them. While GWC’s operations currently depend on fragmented channels like email and voice calls , there is currently no system enabling a traceable, searchable "single thread" that reliably links incoming communication to correct operational objects like PO numbers or shipment references. GWC prefers solutions that can integrate seamlessly with their current ecosystem and those under development.

Your solution should combine conversation understanding in a logistics context (detecting intent, priority, and risk signals ) with advanced data extraction and automated reporting. It must deliver actionable insights into pending, overdue, and at-risk tasks through a centralized cockpit/inbox that provides real-time alerts and triggers escalations the moment SLAs are breached.

The goal is to reduce heavy admin work , improve response times for routine communications , and enhance customer satisfaction through a transparent, automated, and scalable multilingual communication management solution

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How might we create an AI communications co-pilot for logistics operations by triaging, clarifying and escalating time-critical messages across communication channels?

GWC’s day-to-day logistics operations depend on fast, accurate communication across many fragmented channels. Today, these channels are primarily email and voice calls. Because these conversations are scattered and unstructured, teams spend more time than necessary to build a complete, real-time picture of what is happening for a given purchase order, shipment, or job. This is more relevant now that communication channels are expanding to include Voice (phone calls), WhatsApp, Teams, SMS, Email, and other messaging services.

People must manually search inboxes and chat threads, interpret messages, and piece together context across time zones and multiple stakeholders, which slows down execution and increases the chances of errors. Communication is often also ambiguous or incomplete, requiring immediate follow-up for more precise answers (f.e, ‘the truck is on its way’, when will it arrive, where is it?).

This fragmentation and ambiguity increase the chance of late escalations and reactive firefighting. Critical messages can be missed, and clarity on ownership is complicated when multiple internal users and multiple external recipients are involved. Late follow-ups create customer frustration and increase the risk of SLA breaches. A key pain point is reliably linking each incoming communication to the correct operational object (e.g., PO number, shipment/job reference) and automatically routing it to the right internal owner(s), while maintaining a traceable, searchable “single thread” with unique identifiers so anyone can quickly see the latest status and actions required.

GWC Logistics is therefore looking for an intelligent “air-traffic-control” layer, a unified communications co-pilot that sits on top of existing channels rather than replacing them. This layer should understand intent, priority, and risk; extract and connect the right data fields from messages; and present users with a cockpit/inbox that shows what’s pending, overdue, and at risk. It should reduce heavy admin work (copy-pasting into internal tools in the GWC ecosystem. The solution should enable multilingual operation suitable for the Qatar environment, and automate follow-ups/escalations based on SLAs while keeping humans in the loop for actual exception handling and customer/vendor responses.

Technical requirements:

Channel coverage: at a minimum the solution must cover email (Outlook) and voice calls (through speech-to-text transcription) in the pilot phase. For full commercial rollout other channels such as WhatsApp, Teams and text messages should also be integrated.
Conversation understanding in logistics context: the solution must have the necessary intelligence to detect intent, priority and risk signals.
Multi-lingual: support for English and Arabic languages in the pilot phase. Additional languages such as Urdu, Hindi, and Bengali, are a requirement for a full commercial rollout.
Data extraction and reporting: the solution should extract job identifiers such as PO numbers, shipment references and operational data such as arrival times, warehouse and dock identification and update critical business systems.
Ambiguity detection and clarification: it should detect vague replies and automatically request specific, actionable details.
SLA awareness: escalation triggers based on SLAs should be configurable and the system should follow the escalation logic.
Multi-party routing and ownership: support distribution of communication to the right internal owner or team and handle cases where the counterparty is also multi-user.
Integration: integrate with current systems and systems that are currently in development.
Human-in-the-loop (HITL) operation: the solution should initially operate as a co-pilot and progressively support higher levels of autonomy.
Legal and other compliance requirements: Qatar's Personal Data Protection Law (PDPPL), telecommunications regulations for automated communications, enterprise security standards (SOC 2, ISO 27001) and applicable guidelines for relevant communication platforms.

Performance Criteria:

Productivity improvement: a significant increase in the number of suppliers/stakeholders managed per staff member (3-5x in the longer term)
Routine communications: a significant reduction in the time spent on routine follow-up communications (longer term target 70%+)
Faster response times: a reduction in response times for routine communications
SLA risk reduction: earlier detection of potential SLA breaches, fewer missed escalations and ultimately a reduction in SLA breaches attributable to missed or delayed communications.
Data capture quality: an overall increase in the accuracy of data in our systems
Customer satisfaction: upon achieving the above performance criteria the solution should also contribute to an uplift in overall customer satisfaction
AI-Assisted Resolution Rate: Share of communication threads where the AI successfully triages, routes, extracts data, and triggers follow-ups with minimal human input. (Target: 50–60% in pilot, increasing over time)

Cost targets for the commercial phase will be determined on a case-by-case basis and are dependent on the ability to achieve the stated performance criteria (number of suppliers/stakeholders managed per staff member a.o.).

Phase 1: POC Development: Q3 – Q4 2026
Phase 2: Commercial roll-out: To be determined on a case-by-case basis

If the solution is successful, GWC Logistics is willing to support a further roll-out across departments and geographies. Additionally, we are open to solution providers deploying their solutions alongside other players.

Please note that GWC Logistics operates throughout the GCC and offers a wide range of logistics services across various industries. The initial pilot is envisioned to focus on the freight forwarding business only so there is ample opportunity for a significant commercial rollout.

Cash contributions:
QRDI to provide a cash contribution of up to US$100,000 for pilot development.

In-kind contributions:

Mentorship and support for solution development, access to relevant datasets, pilot suppliers and customers, access to subject matter experts from operations, procurement and customer service teams and IT infrastructure and security guidance.

We are looking for SMEs and startups with solutions that can be implemented in a relatively short time frame (TRL of 5 and higher).

Intellectual Property Rights

Background IP (BIP): Each party shall retain all rights, titles, and interests in their respective BIP introduced to the project.
Foreground IP (FIP) Ownership: GWC Ownership: GWC shall retain all IP rights to AI models trained or fine-tuned specifically using GWC’s proprietary data. Solution Provider Ownership: The Solution Provider shall retain ownership of all other FIP created during the project, including training and fine-tuning methodologies.
Commercialization & Territorial Rights: GCC Region: GWC shall have the exclusive right to sell, license, and commercialize the FIP within the Gulf Cooperation Council (GCC) member states. Rest of World (RoW): The Solution Provider shall retain the exclusive right to sell and commercialize the FIP in all territories outside of the GCC.

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Seamless Multi-channel Communication for Customer Engagement and Supply Chain Excellence Challenge

How might we create an AI communications co-pilot for logistics operations by triaging, clarifying and escalating time-critical messages across communication channels?

Challenge Statement

How might we create an AI communications co-pilot for logistics operations by triaging, clarifying and escalating time-critical messages across communication channels?

How might we create an AI communications co-pilot for logistics operations by triaging, clarifying and escalating time-critical messages across communication channels?