Data Annotation And Tagging


Annotation and Tagging ensure that data is properly labeled for algorithm training. We help determine the best tagging paradigms based on data types, and continuously monitor gathered data for conformity to specified requirements. Our objective is to provide algorithm-ready data that can be used immediately, without additional analysis or manipulation. We use a combination of automated and manual tools as needed to ensure accuracy. 

ISO Certification:
Our ISO 27001 certification demonstrates that our organization has invested in our people, processes, and technology (tools and systems) to protect our data and provides an independent, expert assessment of whether our data is sufficiently protected.

Annotation and Tagging is a critical stage to ensure that data is properly labeled so machine algorithms can actually learn.

We support a broad range of video and image tagging from humans, objects, documents, and actions like gestures and expressions. Our teams are skilled in an array of tagging technics such as bounding boxes, point labels, semantic segmentation, and classification.

Tagging types include:

  • Video and Image
  • Semantic Segmentation
  • Text and Audio Transcription
  • Audio Segmentation

Data Ingestion

Data purity starts at the point of collection to avoid “garbage in, garbage out.” The cleaner the data, the better the results. We establish the proper data intake and processing parameters for monitoring data collection in real-time to ensure that it is accurately validated, prioritized, and dispatched in the QA process.

Data Triage

Triaging data can often lead to changes in data requirements, such as acquiring new information or prioritizing information differently. Our experts verify the most essential data in any domain. It includes multilingual triage for speech data, efficient grading of human gestures, and accurate recognition of spaces and objects to optimize the user experience.

Related Content

Dogfooding Program for Speech / Voice Products

Q Analysts was hired by a leading social network company to develop and drive a dogfooding program for their popular smart home consumer product. The objective: provide the smart home product hardware devices to the client’s full-time employees to test at home.  The...

Data Collection for Natural Language Processing

Enterprise investments in artificial intelligence (AI) are on the rise. Two-thirds of companies say they've accelerated AI adoption plans, and nearly 90% agree that AI is quickly becoming a mainstream technology. Many of the mission-critical AI solutions used by...

Scaled Eye Tracking Data Collection

Background: A multinational technology corporation that produces computer software, consumer electronics, personal computers, and related services needed to improve its user identification algorithms within very tight timeframes. The firm contracted with Q Analysts to...

Conversational Speech Tone Study

Background: This case study will showcase Q Analysts Data Collection expertise and infrastructure, including our ability to recruit over 300 participants with diverse demographics to provide our client with the high-quality data they needed for human audio data. The...

Testing Smart Home Hardware Devices

Background: Our client, a leading social network company, contracted our QA & Testing team to test their Smart Home hardware products. Their hardware devices allow people to schedule social media events, connect with friends, family and raise awareness across the...

Data Collection in Real-World Home Environments

BACKGROUND Our client, a prominent social network company, hired us to help collect ground truth data for their consumer AR/VR headsets from a diverse range of real-world home environments. We took this project head-on, knowing we would help evolve our client's...

An overview of Ground Truth Data Collection

What is Ground Truth Data? Ground truth data is data collected at scale from real-world scenarios to train algorithms on contextual information such as verbal speech, natural language text, human gestures and behaviors, and spatial orientation. The broad use of the...

The Science of Human Data Collection

What is Human Data Collection?  As the world around us becomes more digitally focused, the way we interact with machines, data and each other is becoming more prominently through touchscreens, gestures, facial recognition, voice commands, and beyond. This...

Best Practices for QA & Testing For AR, VR and MR

What is Augmented Reality (AR), Virtual Reality (VR) and Mixed Reality (MR) Technologies? Augmented reality (AR) and virtual reality (VR) and mixed reality (MR) — or used collectively, XR— are disruptive technologies that will impact many aspects of our lives in the...

Software Quality Assurance Overview

What is software quality assurance?  QA is understanding users’ demands and anticipating what their needs will be, determining the best path for testing the software, and conducting a series of activities in as many scenarios as needed until the software performs at...


Participants Pool

We have a dedicated global team focused on building a pool of tens of thousands of participants for our human focused data studies. Our participant base has been built with different demographics in mind, including ethnicity, race, gender, skin tone, body structure, and age.

Global Outreach

With a global presence on four continents, Q Analysts can scale our delivery capabilities to meet demanding data collection needs anywhere around the world.

Fully Staged Facilities

We have extensive experience with designing and implementing fully-staged customizable environments in our ISO 27001 compliant Q TestLab facilities around the world. These range from offices to home environments like living rooms, bedrooms, dining rooms to sound proofed rooms and various types of simulated retail storefronts.

Send a Message

Contact us now to discuss your project