Tailored Service for Generative AI

With extensive experience in project implementation, management and human-machine interaction data platform, Nexdata provides unsupervised learning data collection, cleaning, curation service, as well as tailored data services for supervised learning phrase.

Multimodal Data

Deliver comprehensive multimodal datasets across vision, video, speech, text, and cross-modal instruction domains to support the development of advanced Gen AI systems.

Text Data

Vast collection of unlabeled text data, multiple context options,Covering all K12 subjects and more than 1,500 full-version textbooks.

Parallel Corpus Data

More than 200 million pairs of massively parallel corpus, support multi-lingual translation, and is continuously expanding.

Supervised Fine-Tuning (SFT) Data

Instruction-following datasets, including 250,000 Q&A pairs, to enhance models’ reasoning, complex instruction compliance, and sensitivity detection capabilities.

Domain-Specific Data

Custom datasets for vertical industries like finance, healthcare, or legal domains to improve model performance on specialized tasks.

Knowledge Graph / Structured Data

Structured datasets and knowledge graphs can enhance models’ reasoning, entity understanding, and information retrieval capabilities.

RLHF

Perform manual ranking and multi-factor scoringaccording to rules for multiple results generated by the SFT-trained model.

Red Teaming

Help customers discover problems with their models in terms of inaccurate information (illusion), harmful content, false information, discrimination, language bias, etc.

Evaluation of Experience

Nexdata's specialized benchmarking and evaluation services helps you gain critical insights into end users' perceptions about your models performence.

Compliance & Security

Nexdata place the utmost emphasis on data security and client trust. We follows Personal Information Protection Act, GDPR, CCPA, PIPC and HIPAA regulations. we have also achieved ISO 27001,ISO 27701 and ISO 9001 qualifications for security and regulatory compliance. Nexdata delivers unparalleled data security, earning the trust of our clients through our adherence to these globally recognized standards.

Case Studies

Large-Scale Image Description Verification and Correction

USE CASE:Large-Scale Image Description Verification and Correction.
CHALLENGE:The client has 500,000 images with auto-generated descriptions, but some are inaccurate or incomplete due to recognition errors and complex scenes.
SOLUTION:Conducted full-scale verification and correction of 500,000 image descriptions with structured quality control and sampling inspection. Delivered high-accuracy corrected annotations, a Common Issues Analysis Report, and technical optimization recommendations to help reduce the client’s future data processing costs. Monthly production capacity reached 300,000 image description corrections.

Image Editing Dataset Collection for Generative AI

USE CASE:Image Editing Dataset Collection for Generative AI.
CHALLENGE:The client required a large-scale, high-quality image editing dataset for generative AI training, covering diverse editing types and scenes with high visual consistency and pixel-level accuracy.
SOLUTION:Collected and produced over 1.5M image editing data pairs (including single-image and multi-image fusion) across multiple editing types such as identity-consistent, structural, hybrid, spatial, and style transfer. Images are ≥2K resolution with pixel-level editing and ≥97% accuracy, supporting applications such as image synthesis and data augmentation.

USE CASE:Unsupervised Data Cleaning.
CHALLENGE:The client is a well-known large model company. It hopes that Nexdata can assist in parsing 10 million PDF papers in different formats and layouts.
SOLUTION:Nexdata assist in parsing 10 million PDF papers in different formats and layouts, and create high-quality unsupervised data, so that it can show better results in the model pre-training stage.

Foundation Model Reinforcement Learning Data Annotation

USE CASE:Foundation Model Reinforcement Learning Data Annotation.
CHALLENGE:The client is a well-known listed AI enterprise who wants to enhance LLM reinforcement learning algorithms.
SOLUTION:Nexdata assists this client in annotating user queries and outputs, while also scoring outputs and sorting outputs with equal scores. With 1 week ramp up time, we selected and trained 250 annotators, using only 6 months time, 5 million pieces data and 1 million piece dataof RLHF tasks have been successful annotated with high quality

USE CASE:Multimodal Data Annotation.
CHALLENGE:The client is an innovative tech enterprise focused on household and corporate carbon management, who are developing its own LLM.
SOLUTION:With the client possesses pre-annotated multimodal data generated by LLM models. Nexdata assists client in manually reviewing and annotating these data, including image caption and bounding box labeling for image object detection.

Why Nexadata