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Lettria NLP Studio

Text Cleaning API

The majority of NLP projects fail before they even get started due to inadequate data management and cleaning. This is due to open-source solutions being hard to set up and maintain while not performing well.

That's why we have a solution that combines data management and cleaning in one single platform + API combinatio

Text cleaning Illustration

See how
Lettria's Text Cleaning API outperforms competing tools

Read a detailed analysis of the performance of Lettria's Text Cleaning API vs. that of unstructured.io. See how Lettria compares and outperforms.

Connect with all your sources

Choose from an expansive collection of data connectors or simply import your own files in various formats.

To ensure privacy, your data is safeguarded in a secure environment only you have access to. This data can be conveniently reused across all of your current and future word processing projects.

Text collection & management illustration sources
Text cleaning Illustration Datasets

Create and manage your datasets

The dataset manager gives you the power to oversee your sources to effortlessly collaborate between teams as well as repurpose the sources for additional NLP projects across your organization. Datasets are transformed into data assets.

A magic wand for text

Manually cleaning up data can be a pain, but our pain is your gain. We have worked hard to automatic this tedious task and make it available to all our users.

Lettria now offers a precise cleaning formula that can be applied to each data type which makes it easy to manage cluttered data, such as speech-to-text transcripts.

Text cleaning Illustration Magic hand
Text cleaning Illustration Datasets

Do this again and again, at scale

The majority of NLP projects fail before they even get started. Pick a tool that allows you to focus on the meaning of your text, not on collecting and cleaning the data.

The key to any successful data science project is the data collection phase.

Patrick Duvaut

Head of Innovation

The key to any successful data science project is the data collection phase.

Patrick Duvaut

Head of Innovation

The key to any successful data science project is the data collection phase.

Patrick Duvaut

Head of Innovation

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