Natural Language Processing
SmartOne accurately transforms your audio, text document and any integrated text content into high quality training data to power your conversational and intent detection models. Our Natural Language Processed services extend from E-commerce relevance tasks to financial specific text detection, customer relationship management and content moderation.
We extract unstructured text from your documents and classify it. Our experienced, multilingual annotators analyze and categorize text based contents with unrivaled levels of precision
Data Entry / Data Extraction
Our transcriptionists convert videos, phone calls, interviews, lectures and other data into text files. We can process altered files and files with quality issues such as crosstalk and noisy backgrounds. We manually review the content to ensure its accuracy.
We transcribe data from speech to text while analyzing and classifying it. We proofread the end documents for maximum accuracy.
We use data mining tools and techniques to extract keywords, specific data and named entities from unstructured data.
Data Classification and Named Entity Recognition (NER)
We provide comprehensive data classification to extract and organize the information that matters to your organization. We classify your structured and unstructured data based on categories, sentiment analysis, file types, metadata, and the project’s overall criteria.
Sentiment and Intent Analysis
Our analysts identify, quantify and classify different types of behaviors, opinions and sentiments in order to obtain insightful opinion data for brands and companies.
We sort irrelevant and/or inappropriate user-generated content based on your platform’s policy and guidelines. Our annotators have a multilingual and cultural expertise to moderate problematic content and profiles over diverse formats (internal forums, social media..)
Our analysts assess and qualify risk levels for various applications, including fraud mitigation in the financial sector, maintenance of industrial machinery and risk detection for autonomous vehicles in order to help build models that recognize the situations requiring an intervention and take appropriate decisions.
Save time and scale your operations with high-quality training data
Data-related tasks take up about 80% of the time of a Data Scientist. Data cleaning and labeling alone consume 50% of that time. Even when these processes are outsourced, human in the loop remains time and cost-intensive. By working with our experienced annotators, you’ll save time on your AI development and receive high-quality data.
Create a virtuous cycle of improvement through bias-free and accurate datasets
Human in the loop is at the heart of AI design and is the key to adress AI fairness issues, reduce biases, and obtain accurate datasets. At SmartOne, we believe in continuous learning and in inclusive recruitment. This allows us to provide a more diverse judgement pool when working on your data.
Work with a socially responsible business
Working with us helps make an impact in Madagascar by providing stable job opportunities to young malagasys from disadvantaged backgrounds. SmartOne now employs over 1,000 members of the local community, many of whom have little or no formal education.
of a data scientist’s valuable time is spent sourcing, cleaning, and organizing data
of the time available remains to perform data science analytics
How we work
At SmartOne, we believe in the value of human capital, environmental protection, and continuous learning.
By constantly training and supporting our labeling teams, we ensure the quality and integrity of the data we process. All team members are working in-house in our secure facility, which guarantees that their rights are respected and their well-being is prioritized.
A flexible workforce of over 1,000 managed annotators, available 24/7, in a secure production site.
Constant, seamless communication with your project team.
A data-labeling workflow involving an innovative setup and launch process, proprietary set of tools and efficient team.
A half-decade of experience in data labeling and the industry's largest track record