Get production-grade datasets, expertly built for your AI
Supercharge your AI with scalable data labeling services delivered by domain-trained teams and expert annotators across 20+ sectors. We manage annotation, validation, and quality control to produce high-quality, human-verified training data. Helping you improve AI model performance
Why choose our data labeling services?
Human Intelligence behind
Better AI
We turn complex real-world data into reliable ground truth through skilled human judgment, rigorous quality systems and scalable operations.
We treat Data Labeling as a discipline, with trained teams, clear standards and responsible working conditions, not low-cost microtasking.
Better data for AI teams. Better work for the people behind it.
Expert-led teams
We build dedicated teams of trained Data Labelers and Domain Experts around the needs of each project. The result is consistent human judgment, deep task understanding and reliable ground truth built to your specifications.
Responsible workforce
Our teams are recruited, trained and managed in-house, giving us full traceability over the people and processes behind your data. No anonymous crowdsourcing, just skilled professionals working within a structured and responsible model.
Dedicated delivery
Every project is led by an experienced delivery manager who oversees onboarding, production, quality and timelines. Workflows continuously adapt to your requirements, with the right combination of human review and automation.
Transparent pricing
Simple, predictable pricing based on the work delivered. No hidden platform fees, complex subscriptions or unexpected costs. You always know what you are paying for and how your budget is being used.
Secure by design
Security, confidentiality and responsible AI principles are embedded into our delivery model. We support demanding data environments with rigorous controls aligned with GDPR, ISO standards and evolving AI regulation.
Quality without compromise
Quality is engineered into every stage of delivery through clear guidelines, calibration, gold standards, multi-level QA and continuous monitoring. The result is dependable training and evaluation data ready for production AI systems.
The ground truth for Frontier AI
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Data Labeling x Computer Vision
We create production-grade image and video datasets for computer vision models, combining trained human expertise, rigorous quality control and seamless integration with your existing data stack. Reliable ground truth, delivered in the format your models require.
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Data Labeling x Gen-AI
We create high-quality, domain-specific datasets for training, fine-tuning and evaluating generative AI models. Our expert teams combine linguistic, technical and business expertise to produce rich, contextual data across prompts, responses, dialogues, code and complex reasoning tasks.
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Content Moderation & RLHF
We provide high-quality human feedback to train, evaluate and align AI systems. From preference ranking and response evaluation to content moderation and safety review, our trained teams deliver the judgment and contextual understanding your models need.
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Document Processing
We transform complex documents into high-quality training data for document AI models. Text, PDFs and scans are structured, annotated and enriched with the context your models need to perform reliably across business use cases and languages.
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Natural Language Processing
We create high-quality multilingual datasets for training and evaluating NLP models. Our teams deliver precise, context-aware annotation across NER, classification, segmentation and semantic tasks, adapted to complex business use cases.
Data Labeling x Computer Vision
We create production-grade image and video datasets for computer vision models, combining trained human expertise, rigorous quality control and seamless integration with your existing data stack. Reliable ground truth, delivered in the format your models require.
Data Labeling x Gen-AI
We create high-quality, domain-specific datasets for training, fine-tuning and evaluating generative AI models. Our expert teams combine linguistic, technical and business expertise to produce rich, contextual data across prompts, responses, dialogues, code and complex reasoning tasks.
Content Moderation & RLHF
We provide high-quality human feedback to train, evaluate and align AI systems. From preference ranking and response evaluation to content moderation and safety review, our trained teams deliver the judgment and contextual understanding your models need.
Document Processing
We transform complex documents into high-quality training data for document AI models. Text, PDFs and scans are structured, annotated and enriched with the context your models need to perform reliably across business use cases and languages.
Natural Language Processing
We create high-quality multilingual datasets for training and evaluating NLP models. Our teams deliver precise, context-aware annotation across NER, classification, segmentation and semantic tasks, adapted to complex business use cases.
Our method
We help Frontier AI Labs and Enterprise AI teams turn complex real-world data into reliable training and evaluation datasets.
With trained in-house Data Labelers, AI Trainers and Domain Experts, we deliver structured, high-quality data tailored to your use case, whether for model training, testing, validation or LLM fine-tuning.
We define the scope
We start by understanding your objectives, data requirements and operational constraints. From there, we design the right delivery approach, team structure and level of domain expertise for your project.
We align on the approach
Within 48 hours, we assess your needs and, where relevant, run a test task to validate the workflow. We then propose a delivery model tailored to your use case, with clear scope, timelines and pricing.
We build your dataset
We deploy a dedicated team of Data Labelers, AI Trainers and project leads to execute the work. Delivery can be managed within our environment or integrated into your existing tools and workflows.
We assure quality
Quality is embedded throughout delivery through clear guidelines, calibration, manual review, inter-annotator agreement checks and automated controls. This ensures reliable outputs aligned with your model requirements.
We deliver production-ready data
We deliver the completed dataset securely and in the format agreed, whether annotated images, video, audio, text or enriched files. The result is training data ready to be used by AI teams.
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Tested and approved by our clients
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!
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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 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.
Why outsource your Data Labeling?
Today, small, well-labeled datasets with ground truth are enough to advance your AI models. Thanks to SFT and targeted annotations, quality now takes precedence over quantity for more efficient, reliable and economical training.
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Artificial intelligence models require a large volume of labelled data
Artificial intelligence relies on annotated data to learn, adapt, and produce reliable results. Behind each model, whether for classification, detection or content generation (GenAI), it is first necessary to build quality datasets. This phase of the AI SDLC involves Data Labeling: a process of selecting, annotating and structuring data (images, videos, text, multimodal data, etc.). Essential for supervised training (Machine Learning, Deep Learning), but also for fine-tuning (SFT) and the continuous improvement of models, Data Labeling remains a key step, often underestimated, in the performance of AI.
Human evaluation is required to build accurate and unbiased models
In the age of GenAI, data labeling is more essential than ever to develop models that are reliable, accurate and free of bias. Whether it is traditional applications (Computer Vision, NLP, Moderation) or advanced workflows such as RLHF, the contribution of domain experts is essential to ensure the quality and representativeness of datasets. Ever more stringent regulatory frameworks require the use of high-quality data sets to "minimize discriminatory risks and outcomes” (European Commission, FDA). This context reinforces the key role of human evaluation in the preparation of training data.
“Data Labeling is an essential step to train AI models that are reliable and efficient. Although it is often perceived as manual and repetitive work, it nevertheless requires rigor, expertise and organization on a large scale. At Innovatiana, we have industrialized this process: structured methods, automated quality controls and the use of domain experts (health, legal, software development, etc.) for your more advanced projects.
This approach allows us to process large volumes while ensuring relevant and high quality data. We help you optimize your costs and resources, so your team can focus on what matters most: your models, use cases, and products.
But beyond performance, we are carrying out an impact project: create stable and rewarding jobs in Madagascar, with ethical working conditions and fair wages. We believe that talent is everywhere — and opportunities should be, too. Outsourcing data labeling is a responsibility, and we turn it into a driver of quality, efficiency, and positive impact for your AI projects.“
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Compatible with
your stack
We use all major data annotation platforms to adapt to your needs — even your most specific requirements.
Secure Data
We pay particular attention to data security and confidentiality. We assess the criticality of the data you want to entrust to us and deploy best information security practices to protect it.
No stack? No prob.
Regardless of your tools, your constraints or your starting point: our mission is to deliver a quality dataset. We choose, integrate or adapt the best annotation software solution to meet your challenges, without technological bias.
Feed your AI models with high quality training data!
