We build custom datasets
for your AI models
Maximize the performance of your AI models (Machine Learning, Deep Learning, LLM, VLM, RAG, RLHF) with high-quality datasets. Ethically outsource your data annotation tasks (image, audio, video, text) for optimal results
Why choose Innovatiana for your Data Labeling tasks?
Many companies claim to provide "fair" Data
Many companies providing Data Labeling services operate in low-income countries on a contractual and often impersonal basis. Data Labelers are not always paid fairly or work in decent conditions. Contrary to this market "trend", we want to offer outsourcing that has meaning and impact!
An inclusive model
We recruit our own team in Madagascar and train them in data processing and AI labeling techniques. We offer our Data Labelers a fair salary, good working conditions and opportunities for career development.
Ethical outsourcing
We refuse the so-called"crowdsourcing" practices: we create stable and valued jobs to offer you Outsourcing that has meaning and impact as well as transparency about the origin of the Data used for AI.
A proximity management
All the tasks entrusted to us are steered by an English- or French-speaking Manager: your privileged contact. He or she will mobilize a team of Data Labelers to meet your objectives and propose a realistic deadline.
Very competitive rates
We offer flexible conditions, for a pricing adapted to your stakes and to your means. We charge by the job (example: "label 50,000 images with bounding boxes"): no subscription, no set-up fees.
Your Data secured
We pay particular attention to Data Security and Confidentiality. We assess the criticality of the Data you wish to entrust to us and deploy the best Information Security practices to protect it.
High quality Data
Our Data Labelers are trained to deliver High Quality Labeled Data to feed your AI models. We mobilize qualified Data Labelers trained in our methodology: for a maximum quality guarantee and a higher level of security.
Our services
.png)
Data Labeling x Computer Vision
Our Data Labelers are trained in the best practices of image and video annotation for Computer Vision. They are involved in the creation of large supervised data sets (Training Data) intended to train your Machine Learning or Deep Learning models. We work directly on your tools (via an online platform) or on our own secure environments (Label Studio, CVAT, V7, etc.). At the end of the project, you retrieve your annotated data in the format of your choice (JSON, XML, Pascal VOC,...) via a secure channel.
.png)
Data Labeling x Gen-AI
Our team brings together experts with varied profiles — linguists, developers, developers, lawyers, business specialists — capable of collecting, structuring and enriching data adapted to the training of generative AI models. We prepare complex data sets (prompts/responses, dialogues, code snippets, summaries, explanations, etc.) using a combination of expert manual research and automated checks. This approach guarantees rich, contextualized and directly usable datasets for the fine-tuning of LLMs in various fields.
.png)
Content Moderation & RLHF
We moderate the content generated by your AI models to ensure quality, safety, and relevance. Whether it is a question of identifying excesses, evaluating factual situations, recording answers or intervening in RLHF loops, our team combines human expertise and specialized tools to adapt the analysis to your business challenges. This approach reinforces the performance of your models while ensuring better control of risks associated with sensitive or out-of-context content.
.png)
Documents Processing
Optimize the training of your document analysis models with precise, contextualized data preparation. We structure, annotate and enrich your raw documents (texts, PDFs, scans) to extract maximum value, with customized human support at every stage. Your AI gains in reliability, business understanding and multilingual performance.
.png)
Procesamiento del lenguaje natural
Lo apoyamos en la estructuración y el enriquecimiento de sus datos textuales para formar modelos de PNL sólidos, adaptados a los desafíos de su negocio. Nuestros equipos multilingües (francés, inglés y muchos otros) trabajan en tareas complejas como el reconocimiento de entidades nombradas (NER), la clasificación, la segmentación o la anotación semántica. Gracias a una anotación rigurosa y contextualizada, puede mejorar la precisión de sus modelos y, al mismo tiempo, acelerar su producción.
Data Labeling x Computer Vision
Our Data Labelers are trained in the best practices of image and video annotation for Computer Vision. They are involved in the creation of large supervised data sets (Training Data) intended to train your Machine Learning or Deep Learning models. We work directly on your tools (via an online platform) or on our own secure environments (Label Studio, CVAT, V7, etc.). At the end of the project, you retrieve your annotated data in the format of your choice (JSON, XML, Pascal VOC,...) via a secure channel.
Data Labeling x Gen-AI
Our team brings together experts with varied profiles — linguists, developers, developers, lawyers, business specialists — capable of collecting, structuring and enriching data adapted to the training of generative AI models. We prepare complex data sets (prompts/responses, dialogues, code snippets, summaries, explanations, etc.) using a combination of expert manual research and automated checks. This approach guarantees rich, contextualized and directly usable datasets for the fine-tuning of LLMs in various fields.
Content Moderation & RLHF
We moderate the content generated by your AI models to ensure quality, safety, and relevance. Whether it is a question of identifying excesses, evaluating factual situations, recording answers or intervening in RLHF loops, our team combines human expertise and specialized tools to adapt the analysis to your business challenges. This approach reinforces the performance of your models while ensuring better control of risks associated with sensitive or out-of-context content.
Documents Processing
Optimize the training of your document analysis models with precise, contextualized data preparation. We structure, annotate and enrich your raw documents (texts, PDFs, scans) to extract maximum value, with customized human support at every stage. Your AI gains in reliability, business understanding and multilingual performance.
Procesamiento del lenguaje natural
Lo apoyamos en la estructuración y el enriquecimiento de sus datos textuales para formar modelos de PNL sólidos, adaptados a los desafíos de su negocio. Nuestros equipos multilingües (francés, inglés y muchos otros) trabajan en tareas complejas como el reconocimiento de entidades nombradas (NER), la clasificación, la segmentación o la anotación semántica. Gracias a una anotación rigurosa y contextualizada, puede mejorar la precisión de sus modelos y, al mismo tiempo, acelerar su producción.
Our method
A team of professional Data Labelers, driven by Data professionals, to help you create and maintain quality datasets for your AI outsourcing needs(data annotation for Machine Learning / Deep Learning or your LLMs!).
We study your needs
We propose a tailor-made assistance, taking into account your constraints and deadlines.We offer advice on your Labeling infrastructure, the number of Data Labelers required according to your needs and the type of annotations to be used.
We find an agreement
Within 48 hours, we do a test (free of charge). We find an agreement which is convenient for you. We do not lock the service: no monthly subscription, no commitment. We bill by the job!
Our Data Labelers process your Data
We are mobilizing a team of Data Labelers at our service center in Majunga (Madagascar). This English- and French-speaking team is led by one of our Managers: your privileged contact.
We carry out a Quality Review
As part of our Quality Assurance process, we review the work of our Data Labelers. This review is based on a series of manual (sample tests) and automated checks in order to guarantee you the highest level of quality!
We deliver the Data
We provide you with the prepared Data( variousdata sets: annotated images or videos, revised and enriched static files, etc.), according to the terms agreed with you (secure transfer or data integrated into your systems).
.png)
You are talking about us
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.
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!
.png)
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, ...).
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.
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!
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!
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.
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.
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.
Why outsource your Data Labeling tasks?
Manual data labeling is an expensive and laborious process but it is the best way to create quality data sets to train your AI models.
.webp)
Artificial Intelligence models require a large volume of labeled data
AI uses data and algorithms to make predictions. To make these predictions possible, a large amount of labeled data is required. Data Scientists therefore spend a large part of their time creating, processing and refining large data sets (images, videos, static and dynamic data). This is what is called "Data Labeling": a laborious, costly and time-consuming task, but a task which is essential to train supervised automatic learning models (Machine Learning or Deep Learning).
Human evaluation is needed to build accurate and unbiased models
Data Labeling has multiple applications, such as Computer Vision, Content Moderation and Natural Language Processing (NLP) techniques. In the future, Data used to build AI models will be subject to regulations such as the European Commission's regulatory framework on Artificial Intelligence, which requires the use of high quality datasets to "minimize risk and discriminatory results".
"Manual or semi-manual Data Labeling is an expensive and laborious process, but it is the best way to create quality data sets to train your models. At Innovatiana, we offer expertise, skilled labor, and automated controls to handle your big data needs at scale. We optimize your costs, processes and free up time for your team. We want you to focus on your AI models, your Use Cases and your products!
Talent is everywhere. Opportunities are not. We want to help fix this injustice by creating jobs in Madagascar, with fair wages and ethical working conditions.
Outsourcing Data Labeling work to a low-income country is a responsibility: we implement ways to put People and Ethics at the heart of your AI efforts!"
.webp)
We won't be stopped by one platform
We use several platforms on the market to adapt to your needs and your most specific requests!
.png){kind=logo}
.png)
.png){kind=logo}
.png)
.png){kind=logo}
.png)
Fuel your AI models with High Quality Training Data!
