Key Features

Utilizes full context from the application environment for improved translation accuracy.
Allows for customization of LLM prompts to tailor translation output to specific needs.
Supports review and refinement by human translators for maximal quality assurance.
Significantly reduces both the time and cost associated with large-scale localization.
Integrations automatically extract contextual data, reducing reliance on manual input.
Includes an AI Playground for testing prompts across various models and contexts before deployment.
Supports connection to multiple LLM providers, including options for self-hosting.
Features smart load balancing across connected LLM providers to mitigate rate limits.

A key differentiator is the system's emphasis on contextual understanding. Tolgee integrates tools that automatically extract context from your application—such as screenshots or descriptions related to translation keys—eliminating the bottleneck of needing developers or designers to manually provide this crucial information. Furthermore, users can supply additional context through project descriptions, language-specific notes, and detailed key descriptions, empowering the translation engine to grasp the specific domain and required tone of voice for truly accurate and natural output.


To ensure the absolute highest standard of quality, the workflow is designed to blend automated speed with human refinement. While the initial output is fast and accurate, human translators are integrated into the process to meticulously review and polish the generated texts. This hybrid approach allows for fine-tuning using an AI Playground where different LLM providers can be tested, custom prompts can be constructed using variables like key data and context, and configurations can be saved as defaults before the final, human-verified deployment.

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