In-house LLM pipeline, $337K cheaper
Part of AI prototyping & MVPsTranslation was a recurring vendor line item with multi-week turnaround that throttled the product team’s release cadence. Cost scaled linearly with the number of locales and strings.
Designed and shipped an in-house pipeline (GitHub Actions + OpenAI APIs) with locale-specific prompts, glossary enforcement, and automated evaluation. Wired it directly into the PR flow so new strings translate on merge.
$337K saved per year at constant quality. Product team ships translations without an external gatekeeper. 12,000+ key-value pairs translated since January 2024 with negligible regression.
This is the canonical Pilot shape: 3 weeks to ship a working in-house pipeline on a single locale, with an evaluation harness and a clear cost-vs-vendor model. If the numbers land, a short Build engagement wires it into your CI and extends it to every locale.
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