High-quality data annotation services for AI training at scale

From Computer Vision to NLP, we deliver quality annotations tailored to your requirements. Our technical expertise, powered by a responsible work model, ensures the reliability of your training data.

Image d'une annotation de maïs

Expert annotation teams

Structured quality assurance

Scalable production workflows

High-quality training datasets

What we do

Computer vision

Image, video, object detection, segmentation, classification, key points and tracking for AI model training.

NLP

Text annotation, named entity recognition, classification, and sentiment analysis for NLP models training.

Audio and Speech

Transcription, voice annotation, speaker identification, audio classification, and data preparation for voice AI and audio processing systems.

3D / LiDAR / GIS

LiDAR point cloud annotation, 3D object detection and segmentation, geospatial annotation (GIS), mapping, and dataset preparation for autonomous systems and AI models.

From raw data to training-ready AI datasets

Every project follows a structured workflow designed to ensure quality, consistency, and scalability from setup to final delivery.

1

Setup

Guidelines, tool setup and team onboarding.

2

Calibration

Sample validation and guideline refinement.

3

Pilot

Real-data testing and quality validation.

4

Production

Scaled delivery with continuous QA monitoring.

Learn more about our methodology

Industries we serve

We help organizations across a wide range of industries build reliable AI systems through high-quality data annotation and validation services.

Agriculture

Retail

Medical

Security

Aerial

Automotive

Government

Industrial

Sports

Bank & Legal

Administration & OCR

MEDIA

How We Ensure Annotation Quality

Delivering high-quality datasets requires more than annotation capacity. Our quality framework combines expert teams, structured workflows, and measurable performance indicators to ensure consistent results at scale.

Read our full guide on maintaining high-quality annotation →

Iterative Learning & Feedback Loops

We go beyond initial briefings by establishing a strategic “Pilot Phase” to calibrate guidelines and real-time feedback loops to resolve complex edge cases.

Tailored Quality Workflows

We implement robust validation methods such as Review, Consensus Voting, or Honeypot (Ground Truth) benchmarks based on project needs.

Quantitative Quality Metrics

We monitor quality using precise KPIs like Accuracy ratios and IoU for geometric precision, ensuring production-ready results.

Nicola Luminari

Head of Data Science at Alteia
Client of People For AI since 2019

“I have a super positive experience with People for AI in general. Unquestionably, they are not only really responsive but also I always get all the answers to my questions very quickly. Additionally, both annotation deadlines and quality is also a top priority for them.”

Try our labeling services

Whether you are a Startup, an NGO, or a global corporation, we offer flexible models adapted to your project’s scale and priority.

Let’s discuss your next AI milestone together.