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Data analysis 2022-10-17

Lettria

5.0(1)

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Collaborative platform for efficient data structuring.

Overview

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Lettria's no-code AI platform for text provides easy, collaborative, and efficient structuring of textual data. The platform helps create a customized natural language processing (NLP) solution and harnesses the complete potential of the user's data.

The platform offers various solutions like voice2CRM, search engine results optimization, and customer feedback analysis. The Lettria platform also provides a range of tools and components to collect, prepare, and annotate text data, such as text collection and management, dictionary management, text labeling, and ontology management.

The Lettria platform also offers a comprehensive text annotation platform, allowing users to focus on the meaning and knowledge within their text. The Lettria platform's primary purpose is to address the growing failure rate of NLP projects.

The intuitive, user-friendly cloud-based platform is designed to increase productivity and automate time-consuming tasks, making it accessible to varying roles like business analysts, product teams, data engineers, and data scientists.

The platform supports the extraction of key information from call transcripts, improving business performance, automatic analysis of customer reviews, and offers pre-trained and customizable multilingual models.

The Lettria platform adapts to various roles, empowers users to create their customized AI engine, provides access to NLP APIs for deploying NLP projects faster, offers a secured infrastructure to clean and prepare text datasets, and saves data scientists from low value-added tasks, allowing them to focus on designing and deploying AI models.

Overall, Lettria's no-code AI platform for text is a powerful tool that efficiently allows users to harness the true potential of their textual data.

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Lettria was manually vetted by our editorial team and was first featured on May 14th 2023.

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Pros and Cons

Pros

Collaborative platform

Efficient data structuring

Customized NLP solutions

Voice2CRM feature

Search engine optimization

Customer feedback analysis

Text collection and management

Dictionary Management

Text Labeling

Ontology management

User-friendly cloud-based platform

Increases productivity

Automates time-consuming tasks

Accessible to various roles

Supports key information extraction

Improves business performance

Automatic analysis of reviews

Pre-trained multilingual models

Access to NLP APIs

Secured Infrastructure

Saves data scientists' time

Textual data harnessing

Text cleaning tool

Taxonomy Management

Comprehensive text annotation

Addresses NLP project failure

Empowers user-driven customizations

Unifies various sub-components

Transfers existing projects easily

Detects sensitive, personal, inappropriate information

Turns raw documents into databases

Sorts documents into classes

Offers high quality NLP studio

Highly valued by data science teams

Allows extraction of key elements

Identifies watchwords, sentiment, figures

Moderation feature

Document structuration

Document classification feature

Data quality management (soon)

NLP Training (soon)

Knowledge Graph (soon)

E-commerce search result improvement

Web Data Analysis

Automates survey analysis

Vocabulary Enrichment

Four times faster operations

Cons

Limited to textual data

Lacks data visualization features

Requires manual data cleaning

NLP training feature pending

Data quality features pending

Lack of offline functionality

Dependency on cloud infrastructure

No clear integration methods

Limited pre-trained language models

Unspecified data security methods

Q&A

What is Lettria?

Lettria is a no-code AI platform that primarily focuses on the efficient structuring of textual data. It helps build a custom Natural Language Processing (NLP) solution to harness the full potential of the user's data. It offers multiple solutions such as voice2CRM, search engine optimization, and customer feedback analysis. The cloud-based platform is designed for various roles like business analysts, product teams, data engineers, and data scientists.

How does Lettria help structure textual data?

Lettria structures textual data through its collaborative platform that includes components like data collection and preparation, dictionary management, text labelling, and ontology management. By providing a comprehensive text annotation platform, it helps focus on the meaning within their text. It also offers an infrastructure to clean and prepare text datasets for NLP projects.

Who can use Lettria's platform?

Lettria's platform can be used by business analysts, product teams, data engineers, and data scientists. It's designed as an accessible tool for these various roles and allows them to automate time-consuming tasks and increase productivity.

How can Lettria help NLP projects succeed?

Lettria helps NLP projects succeed by providing a user-friendly cloud-based platform that eliminates the need to write any code. Users can fine-tune their project specifications without starting from scratch. It offers NLP APIs for faster project deployment, 15 pre-trained and customizable multilingual models, and a secured infrastructure to help train own models. Lettria's platform is aimed to reduce the failure rate of NLP projects.

What are some tools within the Lettria platform?

Some of the tools within the Lettria platform include text collection and management, text cleaning, dictionary management, text labelling, and ontology management. It also offers access to an annotation platform and tools for data quality supervision and NLP training.

What solutions does Lettria offer?

Lettria offers solutions like Voice2CRM, Search Engine Results Optimization, and Customer Feedback Analysis. The Voice2CRM solution transforms sales call data into meaningful insights for customer relationship management. Search Engine Results Optimization enhances e-commerce search results by improving product recommendations. Customer Feedback Analysis automatically evaluates customer reviews to find critical insights.

What is Voice2CRM in Lettria?

Voice2CRM in Lettria is a solution that transforms data from sales calls into knowledge for customer relationship management. It automatically gathers critical information from call transcripts to improve business performance and streamline CRM.

How can Lettria help analyze customer feedback?

Lettria's platform helps analyze customer feedback by automatically scanning and evaluating reviews to reveal critical insights. It helps identify key trends and information from the feedback, making it easier to understand customer sentiment and improve services.

Can I create a customized AI engine within Lettria?

Yes, users on the Lettria platform can create a customized AI engine without having to write a single line of code. It increases productivity and enables quick automation of tasks.

Is Lettria a cloud-based platform?

Yes, Lettria is a cloud-based platform that provides easy and collaborative functionality. Thanks to its cloud-based nature, it can be accessed from various locations, making it convenient for diverse team collaboration.

What roles can benefit from using Lettria?

Roles that can benefit from using Lettria include business analysts, product teams, data engineers, and data scientists. The platform helps to automate tasks, streamline NLP projects, and increase productivity across the board.

Does Lettria offer pre-trained models?

Yes, Lettria offers 15 pre-trained and customizable multilingual models. These models enable users to expedite the deployment of their NLP projects and increase the efficiency of structuring and analyzing textual data.

How does Lettria support text data collection and management?

Lettria supports text data collection and management by turning datasets into data assets. The platform provides tools for data collection, preparation, and annotation of text data, thereby enabling efficient data management and organization.

What is ontology management in Lettria?

Ontology management in Lettria involves enriching existing ontologies within users' projects. Users can directly import ontologies in standard formats such as .RDF and .OWL, thereby facilitating the extraction and structuring of information within texts.

What is the purpose of dictionary management in Lettria?

Dictionary management in Lettria involves creating and maintaining the vocabulary used in the processing and analysis of textual data. This feature helps enhance user-defined taxonomies and improve the accuracy of both the extraction and comprehension of data.

Does Lettria offer a secured infrastructure for data preparation?

Yes, Lettria does offer a secured infrastructure for data preparation. It enables users to collect, clean, and prepare their text datasets in a secure environment, and supports the training of their own models.

What do they mean by 'no-code' AI platform in Lettria?

'No-code' in Lettria refers to the simplicity and user-friendliness of the platform, which allows users to create and manage NLP projects without writing any code. They can build customized AI engines, use NLP APIs, and deploy the projects at a faster rate while not having to delve into low-level programming.

How does Lettria improve business performance through call transcript analysis?

Lettria improves business performance through call transcript analysis by using its Voice2CRM feature. It extracts key information from the call transcripts, providing critical insights that can help in improving business strategies, customer relationship management, and overall business performance.

Does Lettria allow user customization for AI models?

Yes, Lettria does allow user customization for AI models. It provides users with access to 15 pre-trained and customizable multilingual models, enabling faster deployment of NLP projects. Users can also build their own AI engines according to their specific needs and requirements.

How efficient is Lettria in handling text processing projects?

Lettria is extremely efficient in handling text processing projects. It's designed to be four times faster than building a similar platform in-house. The platform helps reduce the failure rate of NLP projects by providing the tools and resources needed to successfully run and manage them.