Breaking Bias in Translation with Lara

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xploring AI’s role in translation, its impact on humans, and why women should embrace tools like Lara to bridge the gender gap in tech.

What makes Lara different?

“Unlike traditional machine translation, Lara doesn’t just provide translations — it carefully considers context, explains its choices, and asks for clarification when it encounters ambiguities. This is especially important in languages where words have gendered forms. Take ‘doctor’ or ‘nurse,’ for example. In many languages, these words change depending on gender, and if you don’t specify, Lara won’t assume. Instead, it asks for clarification. It’s a small but powerful way to prevent bias from creeping into translations. For companies and localization teams, this means more precise, culturally aware translations—without reinforcing bias.”

How does Lara integrate human expertise?

“AI is only as good as the data it learns from. Since our early days in machine translation, we have meticulously collected every translation we produce, curating a dataset of 25 million translated documents—each enriched with professional translators’ reasoning and alternative choices.

This enables Lara to do what standard AI models often miss—pick up on subtle nuances, cultural context, and linguistic complexity. And when something isn’t clear, Lara asks for confirmation rather than guessing. Instead of replacing human translators, it works with them, helping businesses get translations that aren’t just accurate but also resonate in the real world.”

What does Lara mean for today’s workforce?

“Lara simplifies communication between people of different cultures. And each time we break down a language barrier, we open new doors—whether for collaboration, business, or spreading ideas. AI is becoming a powerful force across industries, and today’s language-driven AI tools don’t require deep technical expertise.

That makes AI more accessible than ever, even to those outside of traditional engineering fields. This is especially important for women, who remain underrepresented in AI due to the broader gender gap in STEM. By engaging with AI early—whether through upskilling programs or hands-on experimentation—women can step into leadership roles, drive inclusive innovation, and shape the ethical and practical applications of AI in the modern workplace.”

About Isabelle

Isabelle Andrieu is an entrepreneur and startup investor. In 1999, she and Marco Trombetti co-founded Translated, a translation service provider that pioneered the use of artificial intelligence to assist professional translators. Isabelle is also a co-Founder and the first citizen of Pi Campus, a venture capital firm investing in early-stage tech startups. Additionally, she serves as CEO at Pi School, the educational branch of Pi Campus on AI.