GTS.AI

Overview

Globose Technology Solutions (GTS) is a data-centric AI company focused on the collection and annotation of high-quality datasets for machine learning. As an expert in the field, GTS supports the entire data pipeline for ML teams, delivering the structured, labeled data required to train, validate, and fine-tune robust models. The company positions itself as a leading provider in the AI data ecosystem, catering to organizations that require reliable data assets rather than raw, unstructured information.

GTS offers datasets spanning multiple modalities, including image, video, speech, and text. These datasets are designed for a wide range of supervised and semi-supervised learning tasks, from computer vision and natural language processing to speech recognition and multimodal systems. The company’s core expertise lies in not only sourcing diverse and representative data but also in applying precise annotation standards—encompassing bounding boxes, segmentation masks, transcription, and semantic labels—to ensure that every sample is ready for direct ingestion into model training workflows.

For enterprises and research groups building AI applications, GTS provides a scalable data infrastructure that aligns with model development cycles. Whether the need is for custom data collection, turnkey dataset packages, or iterative annotation services, GTS acts as an extension of the internal ML team. This allows clients to accelerate their experimentation while maintaining control over data quality, cost, and delivery timelines—critical factors in production-grade AI deployment.

In an industry where data quantity and accuracy directly influence model performance, GTS helps bridge the gap between raw data and deployable intelligence. By combining domain awareness, rigorous quality assurance, and a full-spectrum data operations approach, GTS enables organizations to move confidently from model concept to real-world implementation.

Core capabilities

Image Dataset Collection

Sourcing and curating visual data for computer vision models, including diverse objects, scenes, and conditions.

Video Dataset Collection

Providing sequential frame-level data for tasks such as action recognition, tracking, and surveillance analytics.

Speech Dataset Collection

Delivering audio corpora with transcriptions for ASR, speaker verification, and voice assistant development.

Text Dataset Collection

Creating structured and unstructured text datasets for NLP tasks, including classification, sentiment analysis, and Q&A systems.

Data Annotation Services

Offering precise labeling across image, video, speech, and text data—bounding boxes, polygons, semantic segmentation, and entity tags.

Custom Dataset Design

Tailoring data collection and annotation pipelines to match specific model requirements, domain constraints, and performance targets.

Quality Assurance Framework

Applying rigorous multi-stage validation to minimize label noise and ensure consistency across large-scale datasets.

ML Model Readiness

Delivering datasets in common formats with clear schema definitions, making integration into training pipelines straightforward.

Use cases

Training object detection and image classification models using annotated image datasets

Developing autonomous vehicle perception systems with video and LiDAR-style annotated data

Building automatic speech recognition models with transcribed speech corpora

Fine-tuning large language models with domain-specific text datasets

Creating surveillance or retail analytics systems using action recognition datasets

Supporting medical AI research with carefully annotated diagnostic image sets

Enhancing customer support AI via intent classification and sentiment-annotated text data