Globose Technology Solutions
Globose Technology Solutions Pvt Ltd · Other
Globose Technology Solutions (GTS) is an AI data collection and annotation company that builds custom image, video, text, and speech datasets for machine learning teams.
About Globose Technology Solutions
What Is Globose Technology Solutions
Globose Technology Solutions is an Indian data services company that gathers raw material for AI models: photos, video clips, scanned documents, and recorded speech. The work goes past collection. GTS also labels what it collects, runs quality checks on the output, and hands over files a model can train on.
The company sits in a narrow but crowded market. Public datasets cover common objects and clean studio audio. They rarely cover a hospital's scan archive, a stack of fuel receipts, or a warehouse camera feed. GTS fills that gap by recruiting people to capture and annotate data for one client's specific use case. Its contributor network, GTS Dash, lets workers around the world pick up short surveys or long annotation assignments from home.
The company markets these as data annotation services, and the catalog covers four media types rather than one. Two limits matter before you contact sales. There's no published price list, so budgeting starts with a quote rather than a checkout page. And there's no self-serve annotation tool. Every project begins with a requirements conversation, which adds time before the first batch lands.
Getting Started
- Send a written brief through the site's contact form with the data type, volume, target language, and the model you plan to train.
- Walk through scoping with the team, which covers sampling rules, labeling guidelines, and a delivery schedule.
- Approve a pilot batch so you can check label accuracy against your own examples before the full run.
- Receive the finished dataset in the agreed format, then request revisions on any batch that fails your review.
Product Information
A quick look at Globose Technology Solutions's pricing, supported platforms, and performance.
Best for
The users, tasks, and scenarios where this tool fits best.
Users
- Machine learning teams without an in-house labeling crew
- Startups testing a narrow idea
- Research groups working in several languages
Tasks
- Building OCR training sets from receipts, invoices, business cards, and menus
- Training speech recognition or text to speech models
- Assembling video data from CCTV or traffic cameras
Scenarios
- A model performs well in demos and fails on real customer photos
- Your annotation queue outgrew two contractors
- You're localizing a voice assistant
Key features
Custom Image Dataset Collection
GTS gathers images to your specification rather than from a stock library. Typical categories include medical imagery, invoices, and face images, all collected with the labeling rules your model needs. The practical value is control over class balance and edge cases, which generic datasets rarely give you.
Video Data From CCTV and Traffic Footage
The team collects video clips from surveillance and road camera setups, then annotates frames for object or event training. Scene conditions are part of the brief, so night footage or crowded intersections can be requested up front instead of patched in later.
Text and Document Data
Business cards, menus, receipts, tickets, and forms make up the text side of the catalog. Collection includes the scans plus text annotation, which is the combination most document parsing models need. Handwriting and low-quality photos are usually quoted separately because they cost more to label.
Speech and Audio Transcription
Audio work covers recording, transcription, and labeling for ASR, virtual assistants, and text to speech projects. Contributors read scripts or hold short conversations in their own language, then transcribers produce aligned text. This matters for accent coverage, where a single studio voice won't train a model that holds up in the field.
Annotation and Quality Review
Annotation sits on top of collection. GTS applies image and video labeling with a human in the loop, meaning a reviewer checks a share of each batch before delivery. Ask what that share is and how disagreements get resolved, since accuracy guarantees vary by project.
GTS Dash Contributor Network
GTS Dash is the company's global work from home platform, stocked with contributors who speak different languages and handle different media. It gives GTS flexible capacity for large jobs. For clients, the useful part is reach: rare languages and scattered locations become feasible.
Pros and cons
Pros
- One vendor covers image, video, text, and speech collection plus annotation, which cuts the coordination work on multi-modal projects.
- Domain-specific sources such as medical imagery and document scans are part of the standard catalog, not a special request.
- A multilingual contributor network makes speech datasets in less common languages realistic.
- Human review is built into delivery, so errors surface before the dataset reaches your training pipeline.
- Sample dataset pages on the site let you inspect formats and content before you book a call.
Cons
- No public price list, so you can't estimate cost or compare vendors without contacting sales.
- No self-serve tool for uploading data or writing labeling instructions, which pushes small jobs toward slower project scoping.
- Documentation on turnaround times, accuracy targets, and compliance certifications is thin, so you'll need to ask for specifics in writing.
Frequently asked questions
It collects and annotates training data for AI models. That covers image, video, text, and speech datasets, plus the labeling work that turns raw captures into usable training data.
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