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Telecommunications

We simplify data preparation and
data labelling in
telecommunications

Increased customer support, predictive maintenance, network optimization... We annotate your textual, visual or technical data to train AIs capable of streamlining operations, automating interactions and strengthening the quality of service.

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You work in telecommunications

We processed thousands of tickets, calls, technical logs, and infrastructure images to power telecom AIs. From the automatic analysis of messages to the detection of network anomalies to the intelligent sorting of customer requests, our datasets make it possible to deploy reliable and responsive models on an industrial scale.

Proactive network management

AI algorithms can predict potential failures in telecom infrastructures by analyzing data in real time, thus ensuring better quality of service and reducing interruptions.

Personalization of commercial offers

Artificial intelligence allows telecom operators to analyze customer data in order to offer personalized offers adapted to the specific needs of each user, thus increasing their satisfaction

Optimizing network coverage

AI helps analyze geographic and behavioral data to determine where and how to extend or improve network coverage, ensuring better connectivity for users

Why choose Innovatiana?

Data outsourcing with meaning and impact

We believe in ethical outsourcing in the service of artificial intelligence—far from the impersonal crowdsourcing of our competitors. Our commitment: actively investing in the training and continuous development of our Data Labelers & AI Trainers, ensuring lasting expertise and a dedicated team focused on the success of your projects.

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Ethical outsourcing

We build our teams directly in Madagascar, providing them with rigorous training in best practices for data processing and annotation for artificial intelligence. We ensure fair compensation, excellent working conditions, and real opportunities for professional growth

Inclusive model

We champion an inclusive model, firmly believing that human diversity is essential to the quality of data for AI. Madagascar—considered one of the most culturally, linguistically, and biologically diverse islands in the world—offers a unique foundation for creating rich, representative, and reality-grounded datasets

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Hands-on management

Each project entrusted to us is overseen by a Manager specialized in AI dataset creation—your dedicated point of contact. They coordinate a team of Data Labelers assigned specifically to your objectives and ensure clear, realistic timelines

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Competitive pricing

We offer simple and transparent pricing, designed to adapt to your actual needs. You only pay for what you use—task-based, with no subscriptions or hidden fees—featuring custom volumes and formats, all at the best quality-to-price ratio

Those building the AI of tomorrow trust 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.

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

Lehiben'ny Teknolojia, 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

Mpandrindra fandaharana Accelerator, 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)

Use cases in the industry

Our teams structured and annotated corpora of telecom documents (intervention reports, notices, tickets) in order to extract key information (sites, incidents, equipment concerned). Thanks to NLP, these datasets feed tools for research, automated customer support or intelligent document management.

We analyzed thousands of comments, tweets, and social media posts to detect mentions of network issues (cuts, slowness, white spots). This content is classified by type of concern, location, and feeling, in order to feed real-time monitoring dashboards or intervention prioritization models.

We annotated thousands of images taken in the field or by drone to automatically identify relay antennas, network equipment, technical cabinets or poles. Using bounding boxes, polygons, and segmentation, these annotations make it possible to train visual recognition models for automated inventory or predictive maintenance.

Fuel your AI models with high-quality, expertly crafted training data!

👉 Ask us for a quote