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Etiquetado de datos x Computer Vision

Our team of Data Labelers is trained in data annotation techniques (image or video annotation): develop your perception models to locate and identify objects from different classes, categorize objects or even extract structured text from images.

Cajas delimitadoras

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.

Cuboides

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!)

Polígonos

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.

Puntos clave

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!

Líneas y polilíneas

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.

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.

Clasificación de las capas semánticas

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!

Segmentos

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.

Cajas delimitadoras

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.

Cuboides

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!)

Polígonos

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.

Puntos clave

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!

Líneas y polilíneas

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.

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.

Clasificación de las capas semánticas

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!

Segmentos

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.

Nuestro método

Un equipo de etiquetadores de datos profesionales, dirigido por profesionales, para ayudarle a crear y mantener conjuntos de datos de calidad para sus necesidades de externalización de IA(anotación de datos para modelos de Machine Learning, Deep Learning o NLP).

Fase 1
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Estudiamos sus necesidades

Le ofrecemos apoyo a medida, teniendo en cuenta sus limitaciones y plazos. Le asesoramos sobre su infraestructura de etiquetado, el número de Data Labelers necesario para satisfacer sus necesidades y el tipo de anotaciones que debe utilizar.

Paso 2
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Llegamos a un acuerdo

En 48 horas, realizaremos una prueba (gratuita) para ofrecerle un contrato adaptado a sus necesidades. No bloqueamos el servicio: sin abono mensual, sin compromiso. Cobramos por trabajo.

Paso 3
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Nuestros etiquetadores de datos tratan sus datos

Estamos movilizando un equipo de Data Labelers en nuestro centro de servicios de Majunga (Madagascar). Este equipo anglófono y francófono está dirigido por uno de nuestros responsables: su interlocutor privilegiado.

Paso 4
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Realizamos una revisión de la calidad

Como parte de nuestro enfoque de garantía de calidad, revisamos el trabajo de nuestros etiquetadores de datos. Esta revisión se basa en una serie de comprobaciones manuales (pruebas de muestras) y automatizadas para garantizarle el máximo nivel de calidad.

Paso 5
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Entregamos los datos

Le proporcionamos los datos preparados( diversosconjuntos de datos: imágenes o vídeos anotados, archivos estáticos revisados y mejorados, etc.), según las condiciones acordadas con usted (transferencia segura o datos integrados en sus sistemas).

¡Estás hablando de nosotros!

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
Ética de la IA

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
Cofundador, 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
Director de Tecnología, 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 and on transparency/valorization of working conditions!

Louise Block
Coordinador del Programa Acelerador, 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
Jefe de producto, 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.

Equipo Klein Blue
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
Consultor de IA y datos, Solteq Utility Consulting

Innovatiana encarna exactamente lo que queremos promover en el ecosistema de anotación de datos: un enfoque experto, riguroso y decididamente ético. Su capacidad para capacitar y supervisar a anotadores altamente calificados, al tiempo que garantizan condiciones de trabajo justas y transparentes, los convierte en un modelo en su clase.

Bill Heffelfinger
CVAT, DIRECTOR EJECUTIVO (2023-2024)
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Etiquetado de datos Subcontratación ética

Somos profesionales del etiquetado ético de datos

Muchas empresas que prestan servicios de etiquetado de datos operan en países de renta baja sobre una base contractual y a menudo impersonal. Los etiquetadores de datos no siempre reciben una remuneración justa ni trabajan en condiciones dignas. En contra de esta "tendencia" del mercado, queremos ofrecer una externalización que tenga sentido e impacto.

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Externalización ética

Rechazamos las denominadas prácticasde "crowdsourcing": creamos puestos de trabajo estables y valorados para ofrecerle una subcontratación que tenga sentido e impacto, así como transparencia sobre el origen de los datos utilizados para la IA.

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Tarifas competitivas

Ofrecemos condiciones flexibles, con precios adaptados a sus necesidades y recursos. Cobramos por trabajo (ejemplo: "etiquetar 50.000 imágenes con recuadros delimitadores"): sin suscripción ni costes de configuración.

Un modelo integrador

Contratamos a nuestro propio equipo en Madagascar y les formamos en técnicas de procesamiento de datos y etiquetado para IA. Les ofrecemos un salario justo, buenas condiciones de trabajo y oportunidades de desarrollo profesional.

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Un futuro mejor

Queremos contribuir al desarrollo de ecosistemas virtuosos en Madagascar (formación, empleo, inversión local, etc.).

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Sus datos seguros

Prestamos especial atención a la seguridad y confidencialidad de los datos. Evaluamos el carácter crítico de los datos que desea confiarnos y aplicamos las mejores prácticas de seguridad de la información para protegerlos.

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Hacia la adopción de la IA en Europa y Francia

Queremos acelerar la adopción de técnicas de Inteligencia Artificial en Francia y Europa. Creemos en una IA construida éticamente e invertimos en nuestros equipos dedicados al etiquetado de datos.

Diagrama de tratamiento de datos de Innovatiana
Solicite presupuesto: nos pondremos en contacto con usted en 24 horas.

Alimente sus modelos de inteligencia artificial con datos de entrenamiento de alta calidad.