How Tilde future-proofed localisation with XTRF

As content volumes and complexity increased, Tilde needed a localisation platform that could adapt to its workflows, support automation, and deliver deep operational insight. By adopting XTRF, the team built a scalable localisation engine without sacrificing quality or vendor accountability.

CLIENT SNAPSHOT

About Tilde

Tilde is a pioneer in localisation and translation technologies, operating at the intersection of language and AI. As client demands, content volumes, and delivery expectations grew, Tilde recognised that maintaining quality and scalability would require stronger automation, clearer insight, and tighter control over vendor performance.

Industry: Localisation and Translation Services

Founded: 1991

Headquarters: Latvia

The challenge 

Finding a TBMS that could adapt, not constrain

When Tilde began evaluating translation management systems, flexibility was the primary concern. Off-the-shelf solutions felt too rigid and prescriptive, limiting the ability to reflect existing workflows and operational nuance.

The team needed a platform that could adapt to how they worked, not force standardised processes that would slow them down. Visibility was also critical. Without detailed reporting, it was difficult to assess vendor performance, identify bottlenecks, or optimise delivery at scale.

Tilde was looking for a system that could support growth while providing the transparency needed to manage quality and accountability across a complex vendor network.

Why XTRF by XTM

Choosing flexibility and operational insight

XTRF stood out because of its strong customisation capabilities and established reputation within the localisation industry. The platform could be shaped around Tilde’s workflows rather than imposing fixed structures.

One of the deciding factors was XTRF’s reporting depth. The ability to use macro and vertical columns to generate detailed reports for every job gave Tilde a clear view of vendor performance.

This insight allowed the team to refine its vendor database, reward top performers, and address underperformance with data rather than assumptions. For Tilde, this level of visibility was essential to maintaining quality while scaling operations.

 

The solution

Automation and machine translation working together

To keep pace with growing volumes and tight deadlines, Tilde integrated machine translation directly into its localisation workflow. Their adaptive MT engine learns from translator corrections over time, improving output quality while reducing manual effort.

Instead of treating automation and human translation as separate steps, XTRF by XTM allowed translation, review, and automation to work together. The system could identify where machine translation was appropriate, apply it, and route content to human linguists when necessary.

This approach reduced repetitive work for vendors, helped prevent burnout, and ensured that efficiency increased as volumes grew rather than stalling under pressure.

Implementation and partnership

A smooth migration with hands-on support

Moving to a new localisation platform often introduces disruption, but Tilde’s transition was completed smoothly. With hands-on support from the XTRF team, including both in-person and online training, Tilde migrated its processes and assets in under six months.

“Without the support of the XTM team we’d most likely still be struggling to get this new, improved workflow off the ground.”

The speed and precision of the implementation reflected both XTM's responsiveness and its ability to tailor the platform to Tilde’s requirements.

The Impact

Scaling work without losing control

Today, Tilde processes a high volume of translation work through XTRF, with expectations to handle around 70,000 incoming translation tasks per year. This reflects not only increased demand but confidence in the system’s ability to manage complexity reliably.

Detailed reporting, clearer vendor expectations, and automation have reduced manual bottlenecks and improved overall efficiency. Vendor performance is easier to track and manage, and internal teams can focus on optimisation rather than firefighting.

70000 +

incoming translations per year

100 %

Vendor performance visibility

with automated workflows
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See how XTRF adapts to your processes

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FAQs

Why did Tilde choose XTRF over other TBMS platforms?

Tilde prioritised flexibility over rigid feature sets. XTRF could be customised to reflect existing workflows and provided detailed reporting that gave visibility into vendor performance, which was critical for scaling quality and accountability.

How does XTRF help manage vendor performance?

XTRF’s reporting tools allow teams to analyse delivery data at a granular level. For Tilde, this made it possible to refine the vendor database, reward high performers, and address underperformance using clear data rather than assumptions.

How does machine translation fit into Tilde’s workflow?

Machine translation is integrated directly into the localisation process. An adaptive MT engine learns from translator corrections, improving quality over time and reducing repetitive manual work for vendors.

Was the migration to XTRF disruptive?

No. With support from the XTM team and a structured implementation process, Tilde migrated its workflows and assets in under six months. Training was provided both in person and online to support adoption.

Speak to our team to learn more about switching to XTM.

Is XTRF suitable for high-volume localisation environments?

Yes. The Tilde case study shows how XTRF supports large volumes of translation tasks while maintaining control, insight, and quality through automation and reporting.

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