AI data services
AI Annotation & Labeling: Data training your models can trust
Images, video, text, documents, audio, 3D point clouds and LLM data, labelled by trained annotators and checked by people, so your models learn the right thing the first time.
Everything we do in AI annotation
Eight areas, one team. Pick what you need or combine them into one data pipeline.
Image annotation
Teach vision models to find, outline and understand what is in a picture.
- Bounding boxes: Tight 2D boxes around every object you care about.
- Polygons: Precise outlines for irregular shapes and overlapping objects.
- Semantic segmentation: Every pixel assigned to a class, from road to sky.
- Instance segmentation: Pixel masks that keep each object separate.
- Keypoints & pose: Joints, landmarks and facial points for pose and gesture models.
- 3D cuboids: Depth-aware boxes for objects in 2D images.
- Polylines & lanes: Lane markings, edges, wires and other thin structures.
- Classification & tagging: Image-level labels, attributes and multi-label tags.
Video annotation
Labels that follow objects and events through time.
- Object tracking: The same object, consistently identified frame after frame.
- Action & event recognition: What happens, when it starts and when it ends.
- Temporal segmentation: Clips split and tagged by scene, activity or topic.
- Frame classification: Key frames labelled for quality, content or safety.
- Video captioning: Clear descriptions of what each clip shows.
Text & NLP
Structure and meaning for language models and search.
- Named entity recognition: People, places, products, dates and your own entity types.
- Sentiment & emotion: Tone, polarity and emotion at sentence or document level.
- Intent & topic classification: What the user wants, for chatbots, routing and analytics.
- Relations & entity linking: How entities connect, linked to your knowledge base.
- Content moderation: Toxicity, spam and policy labels for trust and safety.
- Multilingual data: Labelling and translation across Indian and global languages.
Documents & OCR
Turn invoices, forms and scans into clean, structured data.
- Invoices & receipts: Totals, taxes, line items and vendors extracted field by field.
- Forms & KYC documents: IDs, applications and onboarding forms labelled for extraction.
- Layout & tables: Headers, paragraphs, tables and reading order marked up.
- Handwriting transcription: Handwritten notes and fields turned into text.
- OCR verification: Machine-read text checked and corrected by people.
Audio & speech
Speech and sound data for voice assistants and audio AI.
- Transcription: Verbatim or clean transcripts with timestamps.
- Speaker diarization: Who spoke when, in calls, meetings and interviews.
- Emotion & tone: How things were said, not only what was said.
- Sound event labelling: Alarms, machines, music and other non-speech sounds.
- Accents & languages: Multilingual and regional speech data.
3D & LiDAR
Point clouds and sensor data for robots and vehicles.
- 3D bounding boxes: Cuboids around vehicles, people and obstacles in point clouds.
- Point cloud segmentation: Each point labelled as road, building, vegetation and more.
- Sensor fusion: Camera and LiDAR labelled together and kept in sync.
- 3D object tracking: Objects followed through a moving scene.
LLM & AI data training
Human feedback and examples that make generative AI useful and safe.
- RLHF preference ranking: Compare model answers and rank which is better and why.
- SFT prompt & response writing: High-quality examples written for fine-tuning.
- Red teaming & safety: Probe models for harmful, biased or unsafe answers.
- Model evaluation: Score accuracy, helpfulness and tone against your rubric.
- Conversation data: Realistic multi-turn dialogues for chatbots and agents.
- Search & relevance rating: Judge how well results answer a query.
Data services
Everything around the labels that makes a dataset ready to train.
- Data collection: Images, audio, text and video gathered to your spec.
- Cleaning & de-duplication: Broken, blurry and repeated samples removed.
- Synthetic data: Generated samples to fill rare cases and balance classes.
- Dataset curation: Balanced, representative sets split for training and testing.
- Label audits & re-labelling: Existing labels checked and corrected.
- Format conversion: COCO, YOLO, Pascal VOC, JSONL, CSV or your own schema.
How we work
- Guidelines & pilot: We study your use case, write clear labelling rules with you and prove them on a small pilot batch.
- Team & tooling: Annotators are trained on your guidelines and set up in the right tool for your data.
- Annotation at scale: Work runs in batches, with AI pre-labelling wherever it speeds things up.
- Multi-layer QA: Reviewers check every batch against gold-standard samples, and fixes feed back into training.
- Delivery: Data arrives in your format, on your schedule, ready to train.
Industries we label for
- Autonomous mobility: Vehicles, pedestrians, lanes and signs for driver-assist and self-driving.
- Retail & e-commerce: Product tagging, attributes and visual search.
- Healthcare: Medical images and clinical text, labelled with care.
- Agriculture: Crops, weeds, pests and yield from drone and field images.
- Security & surveillance: People, vehicles and events in CCTV footage.
- Finance & insurance: Claims, KYC and invoices turned into structured data.
- Generative AI teams: RLHF, SFT and evaluation data for LLMs.
- Manufacturing & robotics: Defects, parts and grasp points for factory vision.
Why Signmozo
- People check every label: Each batch is reviewed by a second layer of trained reviewers.
- Clear rules, fewer surprises: Edge cases are written down and agreed before the work scales.
- Your data stays private: NDAs, restricted access and secure file transfer as standard.
- Grows with your roadmap: Scale the team up for a launch and down between releases.
Ways to work with us
- Pilot batch: Prove quality on a small sample before you commit to volume.
- Project: A fixed scope, volume and deadline, priced up front.
- Dedicated team: A trained team working as an extension of yours, month to month.
Frequently asked questions
What kinds of data can you annotate?
Images, video, text, documents, audio, 3D LiDAR point clouds and LLM data training such as preference rankings and prompt-response pairs.
Can you work inside our annotation tool?
Yes. We can work in your existing tool, or set up one of the common tools such as CVAT or Label Studio for your project.
How do you make sure the labels are accurate?
Clear guidelines agreed with you, a pilot batch, a second layer of human review on every batch, gold-standard checks and a feedback loop that retrains annotators on any mistakes.
Is our data kept confidential?
Yes. We sign NDAs, limit access to the people on your project and use secure transfer for every file.
Can we start small?
Yes. Most clients begin with a pilot batch so they can see the quality before scaling up.
What format will we receive the data in?
Whatever your pipeline needs: COCO, YOLO, Pascal VOC, KITTI, JSONL, CSV or a custom schema.