Data Labeling x Gen-AI

Our team is experienced in collecting and preparing data from various sources around a defined theme, in order to feed generative AI projects. This data is then used to create or refine generative models, especially in tasks such as generating images, creating legends, or training multimodal models.

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Image search

Before training models, images must be annotated. And before annotating images, you need to collect them. A lot. Not hundreds, but thousands, sometimes tens of thousands. Our team knows where to look and how to find these “real” images in a short amount of time. By extracting them from the web, for example, using our own scraping tools, then qualifying them manually. No synthetic data generated by an algorithm: we are looking for authentic images for you in order to constitute a quality dataset.

Search for videos or audio clips

Finding videos or audio clips on the Internet is not a particularly complex task in the age of YouTube or TikTok. On the other hand, it is a time-consuming task, with many challenges: video quality, relevance of content, choice of sequences, protection of personal data or even respect for copyright. So you have to find the right data! Do not hesitate to contact us: we have the necessary tools and experience to support you in your most complex data collections.

Image search

Search for videos or audio clips

Search for texts or text snippets

We regularly collect text extracts, around a given theme, in order to prepare data for training your natural language processing (NLP) models, for example. These data, collected in French and English, are categorized and checked to ensure their relevance. This service can be combined with pattern detection services (NER or named entity recognition) or sentiment analysis services. Do not hesitate to contact us to find out more!

Image search

Categorization

We are regularly asked to categorize video sequences to train models or algorithms. Our Data Labelers are used to doing this with the most efficient tools on the market for this type of use case, such as V7. To allow you to keep only useful footage, eliminate noise, and structure your video data.

Segments

Segments, to generate masks on a multitude of images, by managing occlusion or overlays. A job that requires patience, rigor and the use of efficient tools. If you are not equipped, we recommend using CVAT... and using our Data Labelers who are very familiar with this tool!

LiDAR or 3D Point Cloud annotation

LiDAR (3D Point Cloud) annotation is a complex task, which requires Data Labelers to have appropriate training and the use of efficient Data Labeling tools. For this type of use case, we create task forces of experienced Data Labelers, led by a Data Labeling Manager who is an expert in the field.

Semantic Layer Classification

Do you have thousands of unused images? We can classify them and associate semantic attributes with these classes to allow you to filter/search in your images fluidly... or to train a model to do it for you! Do you have a simple case that requires you to classify 1,000 images in 3 different categories? A complex case where 40,000 images must be categorized according to 40 classes and 50 attributes? Contact us, we already did it!

Lines & Polylines

Lines, to delimit sections on an image and train your “Computer Vision” model to recognize and delimit roads, streets, sidewalks,... Because even if your object detection model for your autonomous car is very good, nobody wants their car to mistake a sidewalk for a tree. That's what Lines & Polylines are for.

Keypoints

What more can I say? They're dots — on images. Why do it? Often to train facial detection or recognition models. To detect emotions, expressions,... It's a precision job that requires rigor and resilience... qualities that characterize our Data Labelers!

Polygons

To make it easier to learn your models, you can choose to annotate objects with polygons, delineating objects very precisely to eliminate noise. This will prevent you from annotating items that are irrelevant and could cause confusion in your model. This of course takes a bit longer... but good news, our Data Labelers have been trained in the best tools to label polygons in a reasonable amount of time.

Cuboids

An annotation format similar to the Bounding Box... but in three dimensions! Especially useful for your AI products if you work in the automotive industry (but not only!).

Bounding Boxes

The Bounding Box (or “encompassing box” in Molière's language) is the simplest type of annotation, probably the most common. The complexity of Bounding Boxes labelling tasks is often underestimated — a lack of precision can make learning more difficult or time-consuming. Innovatiana Data Labelers are trained in the best annotation techniques — our approach, which includes mandatory training and quality review, allows us to achieve an optimal level of quality.

Categorization

Segments

LiDAR or 3D Point Cloud annotation

Semantic Layer Classification

Lines & Polylines

Keypoints

Polygons

Cuboids

An annotation format similar to the Bounding Box... but in three dimensions! Especially useful for your AI products if you work in the automotive industry (but not only!).

Bounding Boxes

Notre méthode

Une équipe de Data Labelers professionnels, pilotés par des professionnels, pour vous aider à créer et à maintenir des ensembles de données de qualité pour vos besoins d’outsourcing IA (annotation de données pour les modèles de Machine Learning, Deep Learning ou NLP)

Étape 1

Nous étudions votre besoin

Nous vous proposons un accompagnement sur mesure en tenant compte de vos contraintes et échéances. Nous proposons des conseils portant sur votre infrastructure de labellisation, le nombre de Data Labelers requis en fonction de votre besoin ou encore la nature des annotations à privilégier.

Étape 2

Nous trouvons un accord

Dans un délai de 48 heures, nous faisons un test (gratuit) afin de vous proposer un contrat adapté à vos enjeux. Nous ne verrouillons pas la prestation : pas d’abonnement mensuel, pas d’engagement. Nous facturons à la tâche !

Étape 3

Nos Data Labelers traitent vos données

Nous mobilisons une équipe de Data Labelers au sein de notre centre de services à Majunga (Madagascar). Cette équipe anglophone et francophone est pilotée par l'un de nos Managers : votre contact privilégié.

Étape 4

Nous réalisons une revue qualité

Dans le cadre de notre démarche de "Quality Assurance", nous revoyons les travaux de nos Data Labelers. Cette revue s’appuie sur des séries de contrôles manuels (tests sur échantillon) et automatisés afin de vous garantir un niveau de qualité maximal !

Étape 5

Nous vous livrons les données

Nous mettons à votre disposition les données préparées (datasets divers : images ou vidéos annotées, fichiers statiques revus et enrichis, etc.), selon des modalités convenues avec vous (transfert sécurisé ou données intégrées dans vos systèmes).

Vous parlez de nous !

In a sector where opaque practices and precarious conditions are too often the norm, Innovatiana is an exception. This company has been able to build an ethical and human approach to data labeling, by valuing annotators as fully-fledged experts in the AI development cycle. At Innovatiana, data labelers are not simple invisible implementers! Innovatiana offers a responsible and sustainable approach.

Karen Smiley

AI Ethicist

Innovatiana helps us a lot in reviewing our data sets in order to train our machine learning algorithms. The team is dedicated, reliable and always looking for solutions. I also appreciate the local dimension of the model, which allows me to communicate with people who understand my needs and my constraints. I highly recommend Innovatiana!

Henri Rion

Co-Founder, Renewind

Innovatiana helps us to carry out data labeling tasks for our classification and text recognition models, which requires a careful review of thousands of real estate ads in French. The work provided is of high quality and the team is stable over time. The deadlines are clear as is the level of communication. I will not hesitate to entrust Innovatiana with other similar tasks (Computer Vision, NLP,...).

Tim Keynes

Chief Technology Officer, Fluximmo

Several Data Labelers from the Innovatiana team are integrated full time into my team of surgeons and Data Scientists. I appreciate the technicality of the Innovatiana team, which provides me with a team of medical students to help me prepare quality data, required to train my AI models.

Dan D.

Data Scientist and Neurosurgeon, Children's National

Innovatiana is part of the 4th promotion of our impact accelerator. Its model is based on outsourcing with a positive impact with a service center (or Labeling Studio) located in Majunga, Madagascar. Innovatiana focuses on the creation of local jobs in areas that are poorly served or poorly served and on transparency/valorization of working conditions!

Louise Block

Accelerator Program Coordinator, Singa

Innovatiana is deeply committed to ethical AI. The company ensures that its annotators work in fair and respectful conditions, in a healthy and caring environment. Innovatiana applies fair working practices for Data Labelers, and this is reflected in terms of quality!

Sumit Singh

Product Manager, Labellerr

In a context where the ethics of AI is becoming a central issue, Innovatiana shows that it is possible to combine technological performance and human responsibility. Their approach is fully in line with a logic of ethics by design, with in particular a valuation of the people behind the annotation.

Klein Blue Team

Klein Blue, platform for innovation and CSR strategies

Working with Innovatiana has been a great experience. Their team was both reactive, rigorous and very involved in our project to annotate and categorize industrial environments. The quality of the deliverables was there, with real attention paid to the consistency of the labels and to compliance with our business requirements.

Kasper Lauridsen

AI & Data Consultant, Solteq Utility Consulting

Innovatiana embodies exactly what we want to promote in the data annotation ecosystem: an expert, rigorous and resolutely ethical approach. Their ability to train and supervise highly qualified annotators, while ensuring fair and transparent working conditions, makes them a model of their kind.

Bill Heffelfinger

CVAT, CEO (2023-2024)

Data Labeling Outsourcing éthique

Nous sommes les pros du Data Labeling éthique

De nombreuses sociétés fournissant des services de Data Labeling opèrent dans des pays à faible revenu sur une base contractuelle et souvent impersonnelle. Les Data Labelers ne sont pas toujours payés équitablement ou ne travaillent pas dans des conditions décentes. Contrairement à cette "tendance" du marché, nous voulons proposer une externalisation qui a du sens et de l’impact !

Une externalisation éthique

Nous refusons les pratiques dites de "crowdsourcing" : nous créons des emplois stables et valorisés pour vous proposer une externalisation qui a du sens et de l’impact ainsi qu’une transparence quant à l’origine des données utilisées pour l’IA.

Des tarifs compétitifs

Nous proposons des conditions flexibles, pour un pricing adapté à vos enjeux et à vos moyens. Nous facturons à la tâche (exemple : "labelliser 50'000 images avec des bounding boxes") : pas d’abonnement, pas de frais de mise en service.

Un modèle inclusif

Nous recrutons notre propre équipe à Madagascar et nous la formons aux techniques de traitement de données et de labellisation pour l'IA. Nous leur offrons un salaire équitable, de bonnes conditions de travail et des possibilités d'évolution de carrière.

Un avenir meilleur

Nous voulons contribuer au développement d’écosystèmes vertueux à Madagascar (formation, emploi, investissements locaux, …).

Vos données sécurisées

Nous portons une attention particulière à la sécurité et à la confidentialité des données. Nous évaluons la criticité des données que vous souhaitez nous confier et déployons les meilleures pratiques de sécurité de l’information pour les protéger.

Vers l’adoption de l’IA en Europe et en France

Nous voulons accélérer l’adoption des techniques d’Intelligence Artificielle en France et en Europe. Nous sommes partisans d’une IA construite de manière éthique et nous investissons dans nos équipes dévouées à la labellisation des données.

Schéma traitement des données Innovatiana

Feed your AI models with high-quality training data!

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