Automotive Localization at Scale
A global automotive client's localization volume was growing faster than its delivery model could keep up with. LangOptima scaled the program — more output, steadier turnaround, stronger quality — without a matching rise in manual project management.
The challenge
The client's localization program was growing quickly, and delivery was under strain: turnaround-time pressure against existing service commitments, workflow bottlenecks across assignment and file handoff, tooling limits (notably segmentation problems in Lokalise for certain file types), quality risk during volume spikes, and account risk wherever communication wasn't proactive. The brief: scale output without a proportional rise in manual project management.
What we did
A combined operational and technical approach across four fronts:
- Turnaround time. Baseline analysis, triage and escalation, automated task orchestration; large orders split into parallel workstreams; direct source-to-target resourcing to avoid pivoting through English; dynamic linguist assignment and automated late-risk alerts via XTRF.
- Workflow re-architecture. An offline XLIFF pipeline — export from Lokalise, segment in Phrase, automate project creation through XTRF, then sync finalized files back — to bypass the segmentation constraints slowing linguists down.
- Quality at scale. Automated pre-QA screening (Auto LQA) focused human attention where it mattered, with hybrid validation in the CAT workflow and post-delivery sampling for scorecard reporting.
- Account development. A regular business-review cadence, consultative guidance on source-file preparation, partner escalation loops, and daily internal alignment.
The result
Within three to six months, the delivery model became more predictable and scalable: steadier turnaround on high-risk order types and top language lanes, faster job starts with fewer manual handoffs, higher linguist productivity on previously problematic file types, stronger quality governance, and visibly higher client confidence through regular reviews and responsive escalation.
Led by Mihai Petrescu (Solutions Architect), LangOptima. Tools: Lokalise, Phrase, XTRF, Auto LQA.