Qargo expands AI-driven transport management with $33M Series B
Qargo has closed a $33 million Series B led by Sofina, with participation from existing investor Balderton Capital. The company has scaled across major European logistics hubs over the last 18 months. Total funding now stands at $54 million.
For operators and execs, the pitch is simple: lower operating costs, faster execution, and stronger security across the transport stack.
What Qargo does
Founded in 2020, Qargo is a cloud-based TMS for carriers, freight forwarders, and 3PLs. It digitises the full transport cycle-order entry, planning, load building, invoicing, and reporting-while integrating with existing tools. The goal is efficient, profitable operations that scale, with a smaller environmental footprint.
AI that actually moves the needle
Qargo Intelligence automates large chunks of the end-to-end workflow: order creation, route planning, trip optimisation, load building, invoicing, and warehouse time-slot booking. Customers report up to a 75% reduction in repetitive admin, freeing hundreds of hours each week across planning, customer service, and back-office teams.
The platform now includes agentic AI that can interact with external systems, cutting overhead and speeding up processes beyond what traditional TMS setups can deliver. Optimisation features help reduce empty running by up to 30%-useful in a market squeezed by competition, decarbonisation requirements, and rising cybersecurity risks.
Momentum by the numbers
- Annual customer invoicing processed: up from £420 million to more than £1.9 billion since May 2024.
- Customer base: from roughly 100 to more than 400 in the same period.
- Funding: $33 million Series B; $54 million total raised.
- Investors: Led by Sofina with participation from Balderton Capital.
Why this matters for operations leaders
If you run transport, you're judged on margin, reliability, and risk. Qargo is positioning itself as a way to reduce manual effort, cut empty miles, and tighten billing cycles-while improving security across daily operations.
- Fewer manual touchpoints: reduce error rates and handoffs across planning and invoicing.
- Lean fleet operations: optimise routes and loads to reduce empty running and fuel waste.
- Faster cash cycle: standardised, automated invoicing and reporting.
- Fit with current tools: integrate instead of rip-and-replace to protect existing investments.
Questions to ask your team
- Which workflows eat the most hours each week (order entry, planning, invoicing)? What can be automated first?
- What's our current empty running baseline? How do we measure and improve it monthly?
- Which systems must integrate with a TMS (ERP, WMS, telematics)? Where do we have data gaps?
- How quickly do we move from completed job to invoice sent? Where are delays introduced?
- What controls are in place to manage user permissions and reduce cybersecurity exposure?
What's next
With the Series B, Qargo plans to scale its team, expand into new markets, and accelerate development of its AI-driven product capabilities. The company says it will maintain independence and continue partnering with businesses ranging from family-run firms to large enterprises.
If you're planning a skills upgrade for your team around AI operations and automation, you can explore focused training options at Complete AI Training.
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