From Manual Localisation Bottlenecks to Real-Time Market Readiness
How Wamo eliminated translation delays and launched features simultaneously across countries
August 26, 2026 | United States
Executive Summary
For Wamo, the pan-European electronic money institution, speed to market is a competitive advantage. With simultaneous multi-market launches, continuous product updates, and regulated content requirements across multiple languages, localisation needed to operate at the same pace as the product. Manual, fragmented workflows delayed releases across markets and introduced operational overheads.
Uber AI Solutions implemented a system-level translation pipeline that reduced manual work by up to 90% and enabled simultaneous multi-market launches.
Key Results
80-90%
Reduction in manual localisation effort
Less than 1–2 days
Localisation turnaround time reduced from 3–5 days to less than 1–2 days
From 1- 2 to 3-4
Expanded automated simultaneous handling of multiple locales
When Global Expansion Outpaced Localisation Capabilities
Wamo's growth depends on entering new markets quickly — and communicating with customers in their own language. As a rapidly scaling fintech operating across multiple markets, localisation needed to keep pace with the product, not slow it down.
New market launches stalled because translated content fell behind. Instead of a smooth rollout, each new market brought delays, fragmentation, and increased coordination overhead.
Localisation went from being a workflow issue to a limitation on scaling.
"
For a fintech operating across multiple markets, localisation isn't a translation problem, it's an infrastructure problem.
"
Yanki Onen,
Founder, Co-CEO – Wamo
The Hidden Operational Cost of Fragmented Translation Workflows
Localisation breaks at scale when continuous product updates meet fragmented workflows. Content originates across systems, changes constantly, and requires precise, regulated translation. Without system-level coordination, even small updates create delays, inconsistencies, and risk.
“
We needed it [localisation] embedded into how we
build and ship, not bolted on at the end.
”
Yanki Onen,
Founder, Co-CEO – Wamo
Designing a Scalable Localisation Architecture for Growth
Wamo recognised that localisation would have to be embedded into its product workflow if the company was to meet its growth ambitions.
Uber AI Solutions has introduced a system-level localisation model designed for ongoing product updates:
Automation at the system level—not at the task level
Data-driven decision-making for routing, quality, and cost
A hybrid architecture combining machine translation and human review
Continuous synchronisation between content systems and translation workflows
Wamo gained speed and control at scale—without increasing operational overhead.
Building a Continuous Localisation Pipeline Across Systems
The Uber system for Wamo operated as a continuous localisation layer:
- Content changes triggered translation automatically
- Routing logic assigned work based on quality, speed, and cost
- Machine translation and human review operated in a coordinated cycle
- Outputs were reintegrated into production systems in real time
Unlike traditional localisation models, speed increased without sacrificing control, quality, or consistency.
Measurable Impact
The results were immediate and structural.
Manual effort reduced by 80–90%
eliminating the coordination burden that had previously slowed delivery.
Localisation time reduced to less than 1–2 days
from 3–5 days, allowing content to move quickly from creation to deployment.
Fully automated simultaneous handling expanded to 3–4 locales
from just 1–2.
When a new feature is shipped, it goes live everywhere at once
whereas previously, feature releases were rolled out at different times across markets.
Cost reduced
through translation reuse and automated matching, reducing repetitive work across languages.
“
Working with Uber AI Solutions gave us the
system-level approach that matches how we operate.
”
Yanki Onen,
Founder, Co-CEO – Wamo
Enabling Real-Time Global Product Deployment
Now that localisation is built into how Wamo operates, the company can:
- Launch features simultaneously across multiple countries
- Expand into new markets without increasing operational overhead
- Maintain a consistent product experience across languages
- Respond to content changes in real time
- Build trust through accurate, localised communication
By partnering with Uber AI Solutions, Wamo transformed localisation from a scaling constraint into a system that enabled real-time global deployment.
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Testimonials reflect individual results. Individual results do not guarantee the outcome for any given customer, and customer experience will vary.