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Anand Creations
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Beekeeper · Enterprise · Communications

In-house LLM pipeline, $337K cheaper

Part of Transform your operations with AI
Python OpenAI GitHub Actions Evals
serving cost saved / year
The problem

Translation 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.

The approach

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.

The result

$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.

How you'd scope this today

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 full-system build wires it into your CI and extends it to every locale.

AI Transformation Sprint Recommended starting point
From CHF 38,000 / fixed 3 weeks, weekly working software
Ship the full system
Custom quote · typically CHF 40–80k for the build 6 to 12 weeks, weekly working software
Signals from the field

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