Services

Ground-truth data
for every modality.

Trained annotators and multi-stage QA for images, video, 3D point clouds, text, audio and generative AI.

Image & Video

Computer vision annotation

Pixel-accurate labels for detection, segmentation and tracking models, from single images to long video sequences.

Annotation types

  • Bounding boxes
  • Polygons
  • Semantic segmentation
  • Instance segmentation
  • Keypoints & landmarks
  • Polylines & lanes
  • Object tracking
  • Image classification

Common use cases

  • Autonomous driving & ADAS
  • Retail & product recognition
  • Medical imaging
  • Manufacturing inspection

3D & LiDAR

Point cloud annotation

3D labels for perception systems that need to understand depth, distance and motion in the real world.

Annotation types

  • 3D cuboids
  • Point-level segmentation
  • Camera + LiDAR fusion
  • Multi-frame tracking
  • Lane & road markings
  • Ground & free space

Common use cases

  • Autonomous vehicles
  • Robotics & warehouses
  • Drones & mapping
  • Smart infrastructure

Text & Audio

Language and speech data

Structured text and speech datasets for NLP, conversational AI and voice products.

Annotation types

  • Named entity recognition
  • Text classification
  • Sentiment & intent
  • Relation extraction
  • Transcription
  • Speaker diarization
  • Audio event tagging
  • Document & OCR labeling

Common use cases

  • Chatbots & assistants
  • Search & recommendations
  • Call & voice analytics
  • Document AI

GenAI & RLHF

Human feedback for generative AI

Human judgment that helps foundation models become more helpful, accurate and safe.

Annotation types

  • Preference ranking
  • Response rating
  • Prompt & response writing
  • Fact-checking
  • Rubric-based evaluation
  • Safety & red-teaming

Common use cases

  • LLM fine-tuning (SFT)
  • RLHF & reward models
  • Model evaluation
  • Domain-specific assistants
How We Work

One accountable pipeline,from raw data to ground truth.

TagneticAI teams scope, annotate, verify and deliver exactly the data your models need to learn.

  1. Scope
    • data audit
    • label taxonomy
    • guidelines
    • pilot batch
  2. Annotate
    • trained teams
    • tool setup
    • edge cases
    • throughput
  3. Verify
    • consensus review
    • gold sets
    • QA audits
    • accuracy reports
  4. Deliver
    • your format
    • secure transfer
    • iteration
    • scale-up

Ready for training data
you can trust?

Tell us about your project and we'll recommend the right workflow, starting with a pilot on your own data.

Start a projectSee pricing