AI Training Data Services for Machine Learning & Generative AI
Shaip is a leading AI training data provider that helps AI and machine learning teams build accurate, unbiased, production-ready models — from data collection and annotation to LLM fine-tuning and model evaluation, across 65+ languages and 60+ countries.
The Foundation of Every AI Model
What Is AI Training Data?
AI training data is the labeled or structured information used to teach a machine learning model how to recognize patterns and make predictions. The quality, diversity, and accuracy of this data directly determine how well a model performs in the real world.
High-quality AI training data is representative of real-world usage, accurately labeled, balanced to reduce bias, and compliant with data-privacy regulations. Poor-quality data is the leading cause of inaccurate predictions, model hallucinations, and expensive retraining cycles — which is why leading AI teams partner with a specialist AI training data company like Shaip instead of relying on ad-hoc, in-house labeling.
End-to-End AI Data Services
Our AI Training Data Services
Everything you need across the full model lifecycle — from sourcing raw data to fine-tuning and evaluating your model.
Data Collection Services
Custom audio, speech, image, video, and text datasets — real-world, fully consented data collected across 60+ countries and 65+ languages, so your model learns from diverse, representative examples.
Learn more →Data Annotation & Labeling
Pixel-perfect labeling by trained annotators and domain experts — bounding boxes, segmentation, NER, sentiment and intent tagging, and transcription — validated through multi-level QA.
Learn more →Generative AI & LLM Data
SFT, RLHF, prompt–response pairs, human preference ranking, and RAG datasets delivered by subject-matter experts to improve accuracy, reduce hallucinations, and align model behavior.
Learn more →Data Validation & Evaluation
Human-in-the-loop validation, bias and fairness audits, and quality benchmarking to measure and improve model accuracy before and after deployment.
Learn more →Off-the-Shelf Datasets
Ready-to-use, pre-labeled datasets from our data catalog — 30M+ de-identified medical records, 70,000+ hours of speech, and physical-AI scenarios.
Explore the data catalog →Physical AI & Robotics Data
LiDAR and point-cloud annotation, sensor fusion, 3D bounding boxes, robot trajectories, and real-world task scenarios that train autonomous machines, robots, and embodied AI.
See physical AI & robotics →Every Modality, One Partner
AI Training Data by Data Type
For every modality we do both halves of the job — sourcing the raw data you can’t find off the shelf, and labeling it to the standard your model needs. One partner, one QA process, from collection to annotation to delivery.
Text Data Collection & Annotation
We collect: domain-specific text and documents — clinical notes, contracts, chat and support transcripts, and prompt–response sets written by vetted specialists in 65+ languages.
We annotate: NER, sentiment, intent classification, entity linking, and document tagging that turn unstructured text into NLP and LLM training data.
Speech & Audio Collection and Annotation
We collect: scripted, spontaneous, and call-center speech recorded by native speakers across 65+ languages, accents, dialects, and real acoustic environments.
We annotate: transcription, speaker diarization and ID, timestamping, emotion and intent labeling for ASR, voice assistants, and conversational AI.
Image Collection & Annotation Services
We collect: custom image datasets shot to your spec — faces and biometrics, documents and receipts, retail shelves, medical imaging, and edge cases in the lighting and geographies your model will meet.
We annotate: 2D/3D bounding boxes, polygons, pixel-perfect semantic segmentation, landmarks and keypoints.
Video Collection & Annotation Services
We collect: egocentric, multi-camera, CCTV, dashcam, and in-store footage captured by a global contributor network across scripted and in-the-wild scenarios.
We annotate: frame-by-frame object tracking, activity and pose estimation, and event classification for robotics, autonomous driving, sports, and retail video AI.
Physical AI, Robotics & Sensor Data
We collect: multi-sensor captures from real environments — LiDAR, depth, IMU, VR motion capture, teleoperation and robot trajectories across 1,400+ task scenarios and 9 environments.
We annotate: 3D bounding boxes, point-cloud segmentation, sensor fusion alignment, and vision-language labeling for embodied AI.
Synthetic Data Generation & Validation
We generate: representative synthetic text, image, and sensor data where real-world collection is scarce, sensitive, or unsafe to stage — rare events, long-tail edge cases, and privacy-restricted domains.
We validate: human review, bias checks, and blended real-plus-synthetic sets so quality holds up in production.
Human Expertise for Modern AI
Generative AI & LLM Training Data
Building or fine-tuning a large language model requires more than raw text. Shaip delivers the human expertise that makes generative models accurate, safe, and aligned.
Supervised fine-tuning (SFT)
High-quality prompt–response pairs written by domain experts.
RLHF & preference ranking
Human feedback and response comparisons to align model behavior.
RAG & retrieval-augmented data
Domain knowledge bases, document chunking, and query–passage pairs that ground model responses in your own content.
Model evaluation
Hallucination auditing, factuality checks, and quality benchmarking.
Domain-expert data
Prompts, responses, and evaluations authored by vetted specialists in healthcare, legal, finance, and more.
Multilingual coverage
Expert annotators across 65+ languages and specialized domains.
Data for the Real World
Physical AI & Robotics Training Data
Robots, autonomous vehicles, and embodied AI learn from the physical world — and that demands precise 3D, sensor, and motion data. Shaip delivers multimodal, real-world datasets across 1,400+ task scenarios and 9 environments to train perception, navigation, and manipulation.
LiDAR & point-cloud annotation
3D bounding boxes, semantic segmentation, and object tracking on point clouds.
Sensor fusion
Aligned camera, LiDAR, radar, and IMU data for robust multi-sensor perception.
Robot trajectories & teleoperation
Demonstration, action, and manipulation data for imitation and reinforcement learning.
Human activity & pose estimation
Keypoints, gestures, and interaction data for safe human–robot collaboration.
Object detection & tracking
Multi-object detection, classification, and tracking across camera and sensor streams for real-time perception.
Real-world task scenarios
1,400+ scenarios across 9 environments for warehouse, home, industrial, and outdoor robotics.
Why Choose Shaip as Your AI Training Data Provider
Data Collection Capabilities
Create, curate, and collect custom-built datasets (text, speech, image, video) from across the globe based on custom guidelines.
Flexible Global Workforce
Leverage 10,000+In-house global workforce and 500K+ Crowd-scale credentialed contributors. Real-time workforce capacity and efficiency.
Quality
Our proprietary platform & skilled workforce use multiple quality control methods to meet or exceed quality standards.
Diverse, Accurate & Fast
Our process streamlines, the collection process through easier task distribution, & data capture directly from the app & web.
Data Security
Maintain complete data confidentiality by making privacy our priority. We ensure data formats are policy controlled and preserved.
Full lifecycle
One partner across collection, annotation, generative-AI fine-tuning, and evaluation
How It Works
How We Deliver Your Training Data
Security & Compliance
Tell us about your next AI initiative.
From data collection to annotation, licensing, and validation — we'll help you get to market faster, with data you can trust.
Contact UsFrequently Asked Questions (FAQ)
1. What is AI training data?
AI training data is the labeled or structured data used to teach a machine learning model to recognize patterns and make predictions. It can be text, audio, images, video, or multimodal data, and its quality directly determines model accuracy.
2. What is AI training data used for?
It is used to train, fine-tune, and evaluate AI and machine learning models — including computer vision systems, speech recognition, conversational AI, and large language models.
3. What types of AI training data does Shaip provide?
Shaip provides text, speech and audio, image, video, multimodal, physical-AI/sensor, and synthetic data — through collection, annotation and labeling, LLM fine-tuning, and validation services.
4. How does Shaip ensure training data quality?
Every project uses domain-expert annotators and multi-level, human-in-the-loop QA including consensus review, sampling, and bias checks, with quantified quality reporting.
5. What languages and countries does Shaip cover?
Shaip supports 65+ languages and sources consented data from 60+ countries, with a network of 1,000+ vetted data specialists.
6. Is my data secure and which certifications does Shaip hold?
Yes. Shaip is ISO 27001 and ISO 9001:2015 certified, SOC 2 Type II audited, HIPAA compliant, and GDPR/CCPA ready, with PII masking, encryption, and role-based access.
7. Can Shaip provide training data for LLMs and generative AI?
Yes. Shaip offers supervised fine-tuning (SFT), RLHF, human preference ranking, RAG datasets, prompt–response pairs, and model evaluation for large language models and generative AI.
8. Does Shaip provide physical AI and robotics training data?
Yes. Shaip provides physical AI and robotics training data including LiDAR and point-cloud annotation, sensor fusion, 3D bounding boxes, robot trajectories, SLAM and navigation data, and real-world task scenarios across 1,400+ scenarios and 9 environments for autonomous systems and embodied AI.
9. How is AI training data priced?
Pricing depends on data type, volume, annotation complexity, languages, and turnaround. Shaip provides a custom quote after scoping your use case — request a free quote to get started.
10. Does Shaip offer off-the-shelf datasets?
Yes. Ready-to-use, pre-labeled datasets are available from Shaip’s data catalog, including medical records, multilingual speech, and physical-AI scenarios, for licensing.
11. How do I get started with Shaip?
Contact Shaip with your use case to scope a pilot. We align on guidelines and quality targets, then deliver a sample or pilot batch before scaling.
