.png)
We’re on a mission to build
a new NLP paradigm
NLP is living it’s best life. Developed 50 years ago, it’s now in its prime and trending in the field of AI. And we think it’s the biggest thing to come from the open source community.
But here’s the thing..
All of the available models are made by and for English-speaking people. No one is talking about NLP in production. And, people are mainly bragging about model parameters, without any practical use cases
These factors pose major problems for:
Non-native English-speaking data scientists and devs, who struggle with un-auditable multilingual NLP libraries and unreliable open source datasets.
Business managers, who lack concrete solutions for mining their databases for useful information.
That’s where we come in.
%20(1).png)
.png)
We power the next-generation of NLP
Did you know 85% of text processing projects are destined to fail? That’s way too much!
Our platform sets your team up for success by giving you data expert tools without needing to be a data expert.
You can fine-tune your NLP project specs without starting from scratch and without writing a single line of code!
Since 2019, the Lettria team has been committed to resolving the main NLP roadblock & working to democratize the field thanks to simple & collaborative tools.
.png)
To tackle the issues at the heart of NLP, we chose to zero in on a monolingual approach. At the time, we were a young start-up of only 15, so that was also a humble and realistic choice.
Before branching out to English, we started with our native language, French, one of the most complex languages in terms of morphology and syntax, and one of the most dynamic. By 2050, it will be the 3rd most spoken language in the world.
Thanks to two years of R&D and support from the French Ministry of Research as well as other renowned academic institutions, we were able to fashion one of the most performing solutions on the market, now fully functional both in French and English.
Our solutions perform better and more accurately than anything else on the market.
And the confidence in our success means
we can focus on new challenges like:
Lexical
disambiguation
Industrialization of
knowledge graphing-projects
Keep your eyes open for what we build next. 👀
for the gold?