Global supply chains face growing volatility, from geopolitical disruptions and port congestion to rising freight costs and complex billing practices. Despite years of digital investment, international trade still depends heavily on manual coordination between carriers, freight forwarders, suppliers, and internal teams.
Enterprises have invested in ERP platforms, transportation management systems (TMS), warehouse systems, and other systems of record. While these technologies manage critical transactions and data, much of the work connecting them still happens through emails, spreadsheets, phone calls, and manual follow-ups. This creates operational gaps that contribute to higher freight costs, shipment delays, and limited control over business outcomes.
Headquartered in Singapore, GoComet serves over 500 enterprises across more than 70 countries, with over 50 million shipments managed through its platform. As the AI-Native Platform for Global Trade, GoComet helps enterprises move beyond shipment visibility toward greater control over their logistics operations, connecting Planning, Rate Procurement, Compliance, Movement, Disruption Management, and Payment.
With its recently launched Nova, GoComet is taking this further through AI-driven execution, connecting existing enterprise systems, logistics partners, and workflows while enabling specialized AI Workers to handle routine operational coordination.
In this Executive Q&A, GoComet CEO Chitransh Sahai discusses why global trade needs to move beyond traditional systems of record, how AI is changing logistics execution, and what greater control means for enterprise supply chains.
Q. International trade still depends on high levels of manual coordination between freight forwarders, carriers, and internal teams. What systemic inefficiencies led you to build GoComet, and how does your AI-native operating model address them?
Chitransh Sahai: Think about a single shipment leaving a factory. It involves the supplier, freight forwarder, shipping line, customs broker, port, transporter, and warehouse. Every party operates on its own systems and processes, and the shipper's logistics team somehow has to connect everything.
What's interesting is that most large enterprises already have sophisticated technology. They use SAP, Oracle, transportation management systems, warehouse systems, and carrier portals. There isn't necessarily a shortage of software.
The problem is that these systems were primarily designed to record and manage transactions. They weren't built to coordinate all the work happening between different systems, companies, and people.
An ERP might tell you an order has been created. A transportation system might show that a shipment has been booked. But who follows up when the supplier isn't ready? Who checks why the carrier hasn't responded? Who makes sure the final invoice matches the agreed freight rate?
In most companies, people still do that work through emails, spreadsheets, and phone calls.
That's the problem we set out to solve.
We built GoComet around a simple idea: enterprises need more than visibility into their logistics operations. They need control over what happens next.
Our platform connects the decisions across Planning, Rate, Compliance, Movement, Disruption, and Payment. The rate negotiated during procurement should be available when the invoice arrives. A shipment delay should trigger the appropriate follow-up before it affects the customer.
We think of this as a connected Control Engine for global trade.
With our recently launched Nova, we're taking this a step further. Nova is our AI automation and orchestration layer, connecting the enterprise's existing systems, processes, partners, and business rules. It provides the context for specialized AI Workers to perform defined operational tasks, from checking information and following up with carriers to validating documents and escalating exceptions.
Importantly, we're not asking enterprises to replace their ERP or TMS. Those systems remain essential. We're helping coordinate the operational work that happens across them.
For years, enterprises have invested in systems that record the work. We believe the next shift is toward software that can increasingly help get the work done.
People remain responsible for important decisions. Software takes on more of the repetitive coordination.
That's what AI-native means to us.
Q. Global logistics teams frequently struggle with inconsistent freight procurement and opaque quoting practices. How does GoComet's automated rate negotiation empower shippers to secure transparent, competitive pricing?
Chitransh Sahai: Most freight procurement still starts with an email.
A procurement manager sends an RFQ to eight or ten forwarders. The quotes come back in different formats, with different surcharges and commercial terms. The team then spends days bringing everything into Excel just to figure out who's actually offering the best price.
And the lowest headline rate isn't always the lowest total cost.
With GoComet, shippers can bring their forwarders into a structured procurement process. They can compare quotes on an all-in-cost basis, run competitive auctions for spot or contract freight, and award business based on their own commercial rules.
Every quote, negotiation, and award is recorded, so the procurement team knows exactly how a decision was made.
But we also look at freight costs beyond the negotiation itself.
Your freight cost per unit is influenced even before you request a quote. If you're shipping partially filled containers or missing consolidation opportunities, you're already spending more than necessary.
That's why planning and procurement need to work together.
And the process shouldn't end when a rate is awarded.
You might negotiate an excellent rate but lose those savings later through unexpected surcharges, contract deviations, or invoice discrepancies.
By connecting procurement with shipment execution and freight audit, GoComet helps enterprises verify that the rate they agreed to is reflected in what they eventually pay.
Across our customer outcomes, we've reported freight cost reductions of up to 20%. The opportunity comes from making better decisions across the freight lifecycle, not simply negotiating harder with carriers.
Negotiating savings is one thing. Making sure it actually reaches the bottom line is what matters.
That's what greater control over freight costs means to us.
Q. Milestone tracking often fails when cargo moves across fragmented sea, air, and land networks. How does your movement and tracking technology turn raw carrier updates into predictive, actionable shipment intelligence?
Chitransh Sahai: Carrier data is messy. Every shipping line, airline, and transporter reports milestones differently, often with delays and information gaps.
A shipment showing "in transit" for several days doesn't tell a logistics manager whether it's actually going to reach the customer on time.
We bring that information together into a consistent shipment timeline and use historical lane performance, carrier data, and movement patterns to identify potential delays.
For example, if containers on a particular lane normally clear a port in two days but yours has been sitting there for five, that's something your logistics team should know before it becomes a bigger problem.
But the more important change is what happens next.
Traditional visibility platforms tell you something has gone wrong. Someone still has to contact the carrier, understand the reason, assess the impact, follow up, and decide whether to escalate.
For an enterprise handling thousands of shipments, that's an enormous amount of repetitive coordination.
Our approach is to connect shipment intelligence with the workflows required to respond.
If a shipment is at risk, the system can surface the exception, trigger defined follow-up workflows, and route the issue to the appropriate team. With AI Workers, more of the routine checking and coordination can happen automatically within the enterprise's rules and approval boundaries.
The team then focuses on what actually requires human intervention, whether that's expediting cargo, adjusting a delivery commitment, or informing a customer.
That's a very different operating model from simply watching shipments move across a dashboard.
Visibility tells you what's happening. Control is about influencing what happens next.
For logistics leaders, the outcome isn't more tracking updates. It's earlier intervention, fewer avoidable surprises, and stronger on-time delivery performance.
Ultimately, that's how better visibility translates into better business outcomes.
Q. Freight invoice discrepancies, surprise accessorial fees, and detention charges erode shipping margins. How does GoComet automate invoice reconciliation and audit controls to prevent financial leakage?
Chitransh Sahai: Freight invoices are much more complicated than they appear.
One shipment can have fifteen or twenty different charge lines. Each depends on the contract, route, equipment, free-time allowances, exchange rates, and what actually happened during transportation.
Now imagine checking all of that across thousands of shipments and dozens of logistics partners.
Most large enterprises already have sophisticated finance systems. Their ERP can record the invoice, manage approvals, and process payments.
But the difficult question comes before payment: is the amount being billed actually correct?
To answer that, the finance team might need the negotiated freight rate, bill of lading, shipment documents, container movement history, and contractual free-time terms. That information often sits across different teams and systems.
So finance ends up chasing logistics, logistics chases the forwarder, and discrepancies are sometimes identified only after payment.
That's where we come in.
GoComet connects the commercial agreement with the operational shipment record. The platform compares billed charges against negotiated rates, relevant documents, and available movement data to identify potential discrepancies.
Take detention charges, for example. If a carrier bills for additional container days, the team needs to verify whether that charge matches the agreed free-time allowance and the actual movement history.
Instead of manually reconstructing the entire shipment, the relevant information is available for validation, and discrepancies can be flagged before payment approval.
Enterprises can also configure approval thresholds, tolerances, and escalation rules, allowing routine invoices to move through the appropriate process while exceptions receive attention.
This creates an opportunity to move beyond sample-based audits toward more comprehensive invoice validation.
And because procurement, tracking, and freight audit are connected, businesses can understand whether the savings they negotiated were actually realized.
A freight invoice shouldn't be the first time a company discovers what its logistics operations really cost.
The goal is to catch discrepancies earlier, reduce unnecessary payments, and give finance teams confidence in what they're approving.
Q. Recent events like Red Sea corridor diversions and sudden port congestion highlight the fragility of maritime routes. How does your disruption control framework help shippers identify exposure and adjust shipping strategies in real time?
Chitransh Sahai: When something like the Red Sea disruption happens, everyone sees the same headline.
But for a supply chain leader, the headline is only the beginning.
The real questions are: Which of my shipments are affected? Which customers could be impacted? How much time do I have? And what can I still do about it?
That's where disruption intelligence needs to become operational.
We bring together external disruption signals, port congestion information, carrier performance, and shipment data to help enterprises understand how events could affect their logistics network.
Instead of receiving another general alert about a port closure or shipping disruption, logistics teams can identify the relevant shipments and trade lanes and prioritize what needs attention.
The next action depends on the situation.
If a shipment hasn't moved yet, there may still be an opportunity to change the booking, consider another route, or adjust the shipping plan.
If cargo is already in transit, the priority might be reassessing the expected arrival, understanding downstream exposure, or informing the customer early enough to make alternative arrangements.
The same event can also have completely different implications for different companies.
A two-day delay might be manageable for one business. For another, it could mean a production line stops or a critical customer commitment is missed.
That's why disruption management cannot be based on external alerts alone. It needs the context of the enterprise's own shipments, priorities, partners, and operating rules.
This is also where connecting disruption intelligence with planning, movement, and exception workflows becomes valuable. The information needs to reach the people and processes that can act on it.
You cannot prevent every disruption in global trade. But you can improve how early you recognize the risk, how quickly you respond, and how much of the impact reaches your business.
That's what greater control over disruptions should deliver.
Q. Looking toward the future of global enterprise logistics, where do you see the boundary between autonomous AI execution and human operational decision-making over the next five years?
Chitransh Sahai: I think that boundary will move significantly, but it won't disappear.
For decades, enterprises have invested in systems of record. ERPs, transportation systems, and financial platforms are essential because they maintain the transactions, data, and processes that businesses depend on.
But a significant amount of operational work still happens outside those systems.
Someone checks whether a shipment has moved. Someone follows up with a carrier. Someone collects a missing document, compares an invoice, or escalates a delayed delivery.
These are necessary activities, but they don't always require human judgment.
I believe that's where AI will make the biggest difference over the next five years.
Instead of people constantly operating software and coordinating every step, software will increasingly understand the context, identify what needs attention, and carry out the next permitted action.
But there's an important distinction here.
Enterprise logistics isn't a generic workflow. Every company has different suppliers, systems, commercial agreements, approval structures, and risk tolerances.
AI needs to understand those boundaries before it can reliably perform operational work.
That's the thinking behind Nova. It connects the enterprise's existing environment with the logistics capabilities and specialized AI Workers that can carry out defined jobs.
And critically, it keeps enterprise rules, permissions, and human approvals part of the process.
I don't believe human accountability disappears.
People will still decide whether to pay more to expedite a shipment, how to manage an important customer commitment, or when to make an exception to a commercial policy.
What changes is how much routine coordination requires their attention.
There's another consequence that I find even more interesting.
Today, a logistics team might follow up on its twenty most critical delayed shipments because that's all it has time for. A finance team might audit a sample of invoices because checking every line manually is too expensive.
But when software can perform much of that checking and follow-up work, the economics change.
Teams can start monitoring far more exceptions, validating more transactions, and addressing problems that previously went unattended.
The work that never used to get done starts getting done.
So the future isn't simply about doing the same work faster. It's about changing what's operationally possible.
Our long-term vision is for GoComet to become the invisible hand of global trade, where routine coordination increasingly happens in the background and people focus on strategy, relationships, and the decisions that genuinely require their expertise.
Ultimately, trade should just happen.
Conclusion
As global trade becomes increasingly complex, enterprises need more than systems that record transactions or dashboards that display shipment information. They need the ability to connect operational data, logistics partners, and business workflows so that the right actions happen at the right time.
GoComet's AI-native approach brings together logistics capabilities from Planning to Payment, helping enterprises make better freight decisions, respond earlier to disruptions, reduce invoice discrepancies, and eliminate unnecessary manual coordination.
With its enterprise-scale logistics network and the recent launch of Nova, GoComet is working toward a future where existing systems of record remain essential, while AI increasingly handles the operational work connecting them.
For logistics, procurement, finance, and supply chain leaders, the opportunity is clear: greater control over freight costs, service performance, operational risks, and the time their teams spend managing exceptions.
The next era of global trade will not be defined simply by how much information businesses can see, but by how effectively they can act on it.
To learn more, visit: https://www.gocomet.com/
Explore Nova: https://www.gocomet.com/platform/nova
