# Best Data Labeling Software - Page 8

## How Many Data Labeling Software Products Does G2 Track?

**Total Products under this Category:** 130

### Category Stats (Aug 2026)

- **Average Rating:** 4.49/5 (↓0.01 vs Jul 2026) The average rating of products in this category, based on all submitted ratings
- **Top Trending Product:** FiftyOne (+1.01%) - Among all products in this category, FiftyOne recorded the largest rating increase compared to last month

_Last updated: August 20, 2026_

## How Does G2 Rank Data Labeling Software Products?

**Why You Can Trust G2's Software Rankings:**

- 30 Analysts and Data Experts
- 1,800+ Authentic Reviews
- 130+ Products
- Unbiased Rankings

G2's software rankings are built on verified user reviews, rigorous moderation, and a consistent research methodology maintained by a team of analysts and data experts. Each product is measured using the same transparent criteria, with no paid placement or vendor influence. While reviews reflect real user experiences, which can be subjective, they offer valuable insight into how software performs in the hands of professionals. Together, these inputs power the G2 Score, a standardized way to compare tools within every category.

## G2 Grid® for Data Labeling Software
 ![G2 Grid® for Data Labeling Software plotting products by satisfaction and market presence](https://www.g2.com/categories/data-labeling/grids.png?focus%5B%5D=128515&focus%5B%5D=125020&focus%5B%5D=168222&focus%5B%5D=87452&focus%5B%5D=1315312&focus%5B%5D=125450&focus%5B%5D=78925&focus%5B%5D=126287)

Highlighted products: SuperAnnotate, Roboflow, Encord, Amazon Sagemaker Ground Truth, CVAT, Datasaur, Labelbox, and V7 Darwin.

Underlying data: [Grid® JSON](https://www.g2.com/categories/data-labeling/grids.json?focus%5B%5D=superannotate&focus%5B%5D=roboflow&focus%5B%5D=encord&focus%5B%5D=amazon-sagemaker-ground-truth&focus%5B%5D=cvat&focus%5B%5D=datasaur&focus%5B%5D=labelbox&focus%5B%5D=v7-darwin)

**Sponsored**

### Amazon SageMaker

Amazon SageMaker is a fully managed service that enables data scientists and developers to build, train, and deploy machine learning (ML) models at scale. It provides a comprehensive suite of tools and infrastructure, streamlining the entire ML workflow from data preparation to model deployment. With SageMaker, users can quickly connect to training data, select and optimize algorithms, and deploy models in a secure and scalable environment. Key Features and Functionality: - Integrated Development Environments (IDEs): SageMaker offers a unified, web-based interface with built-in IDEs, including JupyterLab and RStudio, facilitating seamless development and collaboration. - Pre-built Algorithms and Frameworks: It includes a selection of optimized ML algorithms and supports popular frameworks like TensorFlow, PyTorch, and Apache MXNet, allowing flexibility in model development. - Automated Model Tuning: SageMaker can automatically tune models to achieve optimal accuracy, reducing the time and effort required for manual adjustments. - Scalable Training and Deployment: The service manages the underlying infrastructure, enabling efficient training of models on large datasets and deploying them across auto-scaling clusters for high availability. - MLOps and Governance: SageMaker provides tools for monitoring, debugging, and managing ML models, ensuring robust operations and compliance with enterprise security standards. Primary Value and Problem Solved: Amazon SageMaker addresses the complexity and resource-intensive nature of developing and deploying ML models. By offering a fully managed environment with integrated tools and scalable infrastructure, it accelerates the ML lifecycle, reduces operational overhead, and enables organizations to derive insights and value from their data more efficiently. This empowers businesses to innovate rapidly and implement AI solutions without the need for extensive in-house expertise or infrastructure management.

[Visit website](https://www.g2.com/external_clickthroughs/record?secure%5Bad_program%5D=ppc&secure%5Bad_slot%5D=category_product_list_llm&secure%5Bcategory_id%5D=2361&secure%5Bchosen_at%5D=2026-08-29T23%3A53%3A04Z&secure%5Bdisplayable_resource_id%5D=2361&secure%5Bdisplayable_resource_type%5D=Category&secure%5Bmedium%5D=sponsored&secure%5Bplacement_reason%5D=page_category&secure%5Bplacement_resource_ids%5D%5B%5D=2361&secure%5Bprioritized%5D=false&secure%5Bproduct_id%5D=52115&secure%5Bresource_id%5D=2361&secure%5Bresource_type%5D=Category&secure%5Bsource_type%5D=category_page&secure%5Bsource_url%5D=https%3A%2F%2Fwww.g2.com%2Fcategories%2Fdata-labeling%3Fpage%3D8&secure%5Btoken%5D=56e121ed862eda0f8844444d50f78994a7cb8eccf3ed61f6f726e5604f781d8a&secure%5Burl%5D=https%3A%2F%2Faws.amazon.com%2Fsagemaker%2F%3Ftrk%3De054ba95-b51d-4594-98bc-aa0239b1797a%26sc_channel%3Ddisplay%2Bads&secure%5Burl_type%5D=custom_url)

### [Picterra](https://www.g2.com/products/picterra/reviews)

Picterra is an enterprise software platform for the training, deployment, and management of machine-learning models powering geospatial applications & business services. Picterra enables organizations to build scalable geospatial products with a geospatial MLOps platform. The entirely cloud-native platform allows users to manage all their data in one place, create, train, and improve models in a collaborative environment, and bring them into production without needing additional resources from IT.

#### Who Is the Company Behind Picterra?

- **Seller:** [Picterra](https://www.g2.com/sellers/picterra)
- **Year Founded:** 2016
- **HQ Location:** Lausanne, CH
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=758d9e29811e7c7baa6a84c7ceeedc8b8c5386f65f8037491a17ae62db8bfc9c&secure%5Burl%5D=http%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fpicterra&secure%5Burl_type%5D=linkedin_company_website)  
29 employees on LinkedIn®

### [Polaron](https://www.g2.com/products/polaron/reviews)

Polaron is an advanced AI-powered platform designed to streamline and enhance the process of data annotation and labeling for machine learning applications. By leveraging cutting-edge artificial intelligence technologies, Polaron automates the traditionally labor-intensive task of data labeling, significantly reducing the time and effort required to prepare datasets for training machine learning models. This automation not only accelerates the development cycle but also ensures higher accuracy and consistency in the labeled data, leading to more reliable and effective AI solutions. Key Features and Functionality: - Automated Data Annotation: Utilizes AI algorithms to automatically label large datasets, minimizing human intervention and expediting the annotation process. - High Accuracy and Consistency: Ensures precise and uniform labeling across datasets, enhancing the quality of data used for training machine learning models. - Scalability: Capable of handling vast amounts of data, making it suitable for projects of varying sizes and complexities. - User-Friendly Interface: Provides an intuitive platform that allows users to easily manage and monitor the annotation process. - Integration Capabilities: Seamlessly integrates with existing machine learning pipelines and tools, facilitating a smooth workflow. Primary Value and Problem Solved: Polaron addresses the critical challenge of efficiently preparing high-quality labeled datasets, which are essential for training accurate and effective machine learning models. By automating the data annotation process, Polaron significantly reduces the time, cost, and potential for human error associated with manual labeling. This enables organizations to accelerate their AI development initiatives, improve model performance, and achieve faster time-to-market for their AI-driven products and services.

#### Who Is the Company Behind Polaron?

- **Seller:** [Polaron](https://www.g2.com/sellers/polaron)
- **Year Founded:** 2023
- **HQ Location:** London, GB
- **LinkedIn® Page:** [uk.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=38ba04679a650ef81013db7fbe9143ab28e837cf02c109824af8eaa16bc9595c&secure%5Burl%5D=https%3A%2F%2Fuk.linkedin.com%2Fcompany%2Fpolaron-ai&secure%5Burl_type%5D=linkedin_company_website)  
15 employees on LinkedIn®

### [Predictly MLOps](https://www.g2.com/products/predictly-mlops/reviews)

Predictly understands how important it is to automate the processes in a business and Predictly is here to help businesses in implementing machine learning with no hassle, which reduces costs and optimizes the overall productivity.

#### Who Is the Company Behind Predictly MLOps?

- **Seller:** [Predictly Tech Labs](https://www.g2.com/sellers/predictly-tech-labs)
- **Year Founded:** 2015
- **HQ Location:** Bangalore, IN
- **Twitter:** @prdictly  
516 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=cc6870c8d1da363ecb9968073b31e4b53b8f1428871b55845ee33654318a074b&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fpredictly-tech-labs%2F&secure%5Burl_type%5D=linkedin_company_website)  
4 employees on LinkedIn®

### [Rapidata](https://www.g2.com/products/rapidata/reviews)

Rapidata is a human feedback platform built for AI teams that need fast, scalable, and high-quality human preference data for reinforcement learning from human feedback (RLHF), model evaluation, and post-training workflows. We help AI labs, model providers, and product teams collect human judgments on model outputs through an API-first platform designed for speed, scale, and flexibility. RLHF depends on reliable human feedback: comparisons, rankings, ratings, and qualitative judgments that help models better align with human preferences. Rapidata makes it easy to collect this feedback from real people across diverse geographies, languages, and demographics. Teams can use Rapidata to compare responses from large language models, evaluate image or video generation outputs, rank model completions, validate synthetic data, assess safety and helpfulness, and generate preference datasets for fine-tuning, reward modeling, DPO, and RLHF pipelines. Unlike traditional data labeling vendors, Rapidata is optimized for modern AI development cycles. Instead of slow, project-based annotation processes, teams can launch feedback tasks programmatically and receive results quickly. This allows researchers and engineers to evaluate model variants, run preference tests, identify failure modes, and iterate on model behavior much faster. Rapidata supports a wide range of human-in-the-loop evaluation workflows, including pairwise comparisons, Likert ratings, classification, ranking, transcription, multimodal evaluation, and custom task designs. The platform is particularly useful for teams working on large language models, generative AI, image generation, text-to-speech, recommendation systems, AI assistants, and other user-facing AI products where human judgment is essential. Our goal is to make human feedback as accessible and programmable as any other part of the AI stack. With Rapidata, teams can collect statistically meaningful feedback from real humans at scale, integrate results directly into their training or evaluation pipelines, and continuously improve model quality based on what people actually prefer. Rapidata helps AI teams move faster from raw model outputs to aligned, high-performing systems by making RLHF and human evaluation workflows scalable, repeatable, and API-driven.

#### Who Is the Company Behind Rapidata?

- **Seller:** [Rapidata](https://www.g2.com/sellers/rapidata)
- **HQ Location:** Zürich, CH
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=22934b6fc25ab0b3102b1b6a6c04e2da2630bdcf347aed0de4d82aa99a84fdea&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Frapidata%2F&secure%5Burl_type%5D=linkedin_company_website)  
14 employees on LinkedIn®

### [RoboFLO AI](https://www.g2.com/products/roboflo-ai/reviews)

RoboFLO AI is a cloud-based SaaS platform designed to transform raw robotics sensor data into training-ready AI datasets efficiently. By automatically ingesting data from various sensors—such as cameras, LiDAR, and IMUs—the platform utilizes advanced AI to label, clean, organize, and version datasets, significantly reducing the time required to develop AI models from months to mere hours. With a pay-per-GB pricing model, RoboFLO AI offers a scalable solution for robotics teams aiming to streamline their data processing workflows. Key Features and Functionality: - AI Auto-Labeling: Automatically labels objects, scenes, and events in sensor data using state-of-the-art AI vision models, eliminating the need for manual annotation. - Smart Data Cleaning: Detects and removes duplicates, corrupted frames, sensor noise, and low-quality samples, ensuring datasets are clean and ready for training. - Dataset Versioning: Provides automatic versioning of datasets, allowing teams to track changes, compare iterations, and collaborate effectively. - ML Pipeline Export: Enables seamless export of training-ready datasets to platforms like PyTorch, TensorFlow, and Hugging Face with a single click. - Multi-Sensor Fusion: Combines data from multiple sensors into unified, synchronized datasets by aligning timestamps and coordinate frames automatically. - Usage Analytics: Offers insights into data volume, labeling accuracy, pipeline throughput, and cost per dataset to optimize data workflows. Primary Value and Problem Solved: RoboFLO AI addresses the significant challenge of processing vast amounts of raw sensor data generated by robots. By automating the labor-intensive tasks of data labeling, cleaning, and organization, the platform accelerates the development of AI models, allowing robotics teams to focus on innovation rather than data preparation. This efficiency not only reduces time-to-market but also enhances the accuracy and reliability of AI models deployed in various robotic applications.

#### Who Is the Company Behind RoboFLO AI?

- **Seller:** [RoboFLO AI](https://www.g2.com/sellers/roboflo-ai)
- **HQ Location:** N/A
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=7886df2ed926834e5eb248c77dcfa8e5c815d3ab1f0fe3132ced0dba45868834&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2FNo-Linkedin-Presence-Added-Intentionally-By-DataOps&secure%5Burl_type%5D=linkedin_company_website)  
1 employees on LinkedIn®

### [Roseman Labs](https://www.g2.com/products/roseman-labs/reviews)

At Roseman Labs we have built a groundbreaking solution to train and use AI on data that is too sensitive to be shared. Our solution is used by 100+ organizations across Healthcare, the Public Sector and Financial Services to solve real world problems. The Roseman Labs platform enables you to encrypt, link and analyze multiple data sets, while safeguarding the privacy and commercial sensitivity of the underlying data. You can combine information from several organizations, run your analyses on the aggregated records, and generate new insights – all without ever being able to view other participants’ input. You get the insights you need, while the data stays protected. Our software employs a cryptographic technology called Multi Party Computation that encrypts all data from beginning to end. This means data owners always stay in control of how their data is processed, enhancing privacy compliance through data minimization and proportionality. Through the ease of a familiar Python interface, you can enjoy 50+ ready to use functionalities, ranging from basic operations to machine learning and regular expressions. These features unlock previously inaccessible information without compromising data privacy, offering more detail into statistics including time efficiency, product effectiveness, cost savings, resource allocation, and risk analysis.

#### Who Is the Company Behind Roseman Labs?

- **Seller:** [Roseman Labs](https://www.g2.com/sellers/roseman-labs)
- **Year Founded:** 2020
- **HQ Location:** Utrecht, NL
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=6480f66a206c9af22d9e89875546c31a683d6d553bf20f03085389033287c120&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Frosemanlabs&secure%5Burl_type%5D=linkedin_company_website)  
35 employees on LinkedIn®

### [Rubii](https://www.g2.com/products/rubii/reviews)

Rubii is an AI-powered platform designed to streamline and enhance the process of data annotation and labeling for machine learning applications. By leveraging advanced artificial intelligence, Rubii automates the traditionally labor-intensive task of data labeling, enabling organizations to accelerate their model development cycles and improve overall efficiency. Key Features and Functionality: - Automated Data Annotation: Utilizes AI algorithms to automatically label large datasets, reducing manual effort and minimizing human error. - Customizable Labeling Workflows: Offers flexible workflows that can be tailored to specific project requirements, ensuring adaptability across various industries and use cases. - Quality Assurance Mechanisms: Incorporates validation processes to maintain high accuracy and consistency in labeled data. - Scalability: Capable of handling vast amounts of data, making it suitable for both small-scale projects and large enterprise needs. - Integration Capabilities: Seamlessly integrates with existing machine learning pipelines and tools, facilitating a smooth transition and implementation. Primary Value and Problem Solved: Rubii addresses the critical challenge of efficient and accurate data labeling in machine learning projects. By automating the annotation process, it significantly reduces the time and resources required for data preparation, allowing data scientists and engineers to focus more on model development and innovation. This leads to faster deployment of AI solutions and a more streamlined workflow, ultimately enhancing productivity and reducing operational costs.

#### Who Is the Company Behind Rubii?

- **Seller:** [Rubii AI](https://www.g2.com/sellers/rubii-ai-b009804c-00d0-4ce0-8ef3-6b1be03f3abd)
- **HQ Location:** N/A
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=7886df2ed926834e5eb248c77dcfa8e5c815d3ab1f0fe3132ced0dba45868834&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2FNo-Linkedin-Presence-Added-Intentionally-By-DataOps&secure%5Burl_type%5D=linkedin_company_website)  
1 employees on LinkedIn®

### [Scematics](https://www.g2.com/products/scematics/reviews)

Scematics is an end-to-end data labeling platform built to streamline the creation of high-quality datasets for AI and ML teams. From precise annotation tools to fully customizable workflows, Scematics empowers organizations to manage, label, and monitor their data efficiently. The platform supports a wide range of data types including image, video and text, with built-in AI assistance for faster labeling.

#### Who Is the Company Behind Scematics?

- **Seller:** [Vision Scematics](https://www.g2.com/sellers/vision-scematics)
- **Year Founded:** 2020
- **HQ Location:** Chennai, IN
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=3982ec9147ec14f8e640b2f3f03b72843661b79c09eb3b522195dd18f37679af&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fscematics&secure%5Burl_type%5D=linkedin_company_website)  
16 employees on LinkedIn®

### [ShaipCloud](https://www.g2.com/products/shaipcloud/reviews)

#### Who Is the Company Behind ShaipCloud?

- **Seller:** [Shaip](https://www.g2.com/sellers/shaip)
- **Year Founded:** 2018
- **HQ Location:** Louisville, Kentucky
- **Twitter:** @weareShaip  
224 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=a89f13d6df67ec1bfdf8e1dd9ec7c38f834538f3a1ac4247c2cb0f7e802aceee&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F66611098&secure%5Burl_type%5D=linkedin_company_website)  
365 employees on LinkedIn®

### [Shotwell AI](https://www.g2.com/products/shotwell-ai/reviews)

#### Who Is the Company Behind Shotwell AI?

- **Seller:** [Shotwell AI](https://www.g2.com/sellers/shotwell-ai)
- **Year Founded:** 2026
- **HQ Location:** N/A
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=3c9bce4955e33205e61f45a74495793080b81b2857d57654ef1b10db0a9f2e2e&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fshotwell-ai&secure%5Burl_type%5D=linkedin_company_website)  
6 employees on LinkedIn®

### [Sovrano AI](https://www.g2.com/products/sovrano-ai/reviews)

Sovrano AI is a European platform dedicated to enhancing the development of artificial intelligence through expert human evaluation. It connects skilled individuals with AI companies to assess and improve AI models, ensuring their outputs are reliable and aligned with human values. The platform offers remote, flexible, and paid opportunities for evaluators across various domains, including finance, law, STEM, marketing, and general business. The process begins with users creating a free account, which requires no university email and is entirely free of charge. After registration, candidates undergo a short skills assessment tailored to their expertise, covering domain knowledge and evaluation abilities. This assessment helps match them to suitable projects from top AI companies across Europe. Once matched, evaluators can start working on tasks such as Reinforcement Learning from Human Feedback (RLHF), data annotation, red-teaming, safety evaluations, response writing, and rating and scoring. These tasks involve ranking AI-generated responses, labeling data, identifying vulnerabilities, crafting ideal responses, and scoring AI outputs based on predefined criteria. Sovrano AI emphasizes the importance of genuine human judgment in the evaluation process. The use of AI tools to perform evaluations is strictly prohibited, as it undermines the purpose of human assessment and can degrade model quality. Evaluators are allowed to use tools for grammar and spelling correction but must rely on their own reasoning and analysis for the evaluation tasks. The platform also offers a referral program, allowing users to refer researchers, labs, or students to join Sovrano AI. Referrers earn a flat €20 for every intern hire or 20% of everything their contractor referrals make, capped at four times the referral's first accepted hourly rate. For students and scholars, Sovrano AI provides structured internships that combine AI education with hands-on evaluation work. These internships are designed to fit various university formats, including part-time semesters, for-credit integrations, and summer intensives. Participants receive mentorship, structured assessments, and certifications upon completion, enhancing their employability in an AI-driven job market. Payments are processed through Deel, a global payroll platform. Evaluators set up their Deel accounts during onboarding, providing personal details, tax information, and bank account or withdrawal methods. Payments are processed in euros, with Deel handling currency conversions if necessary. The earnings dashboard allows users to track their payments, filter earnings by contract or time period, and download payment reports for tax purposes. Sovrano AI's mission is to build the infrastructure for trustworthy AI by leveraging human expertise to validate and improve AI models. By connecting evaluators with AI companies, the platform ensures that AI development is grounded in human consensus, learning, and scalability.

#### Who Is the Company Behind Sovrano AI?

- **Seller:** [Sovrano AI](https://www.g2.com/sellers/sovrano-ai)
- **Year Founded:** 2026
- **HQ Location:** Barcelona, ES
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=4cb781b9871d254fce944224f3207c3da6cf63261d92b9bd55b5fbf0946ba4bd&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fsovrano-ai&secure%5Burl_type%5D=linkedin_company_website)  
43 employees on LinkedIn®

### [Supervisely AI](https://www.g2.com/products/supervisely-ai/reviews)

Supervisely AI is a comprehensive platform designed to streamline the entire lifecycle of computer vision projects, from data annotation to model deployment. It offers a user-friendly interface that simplifies the management of datasets, annotation tasks, and collaboration among team members, making it accessible for both beginners and experts in the field. Key Features and Functionality: - Data Annotation Tools: Provides a suite of annotation tools supporting various data types, including images, videos, and point clouds, enabling precise labeling for training datasets. - Model Training and Evaluation: Facilitates the training of custom AI models with built-in support for popular frameworks, along with tools for evaluating model performance. - Collaboration and Project Management: Offers features for team collaboration, including role-based access control, task assignment, and progress tracking to enhance productivity. - Integration and Deployment: Supports seamless integration with existing workflows and enables deployment of models to various environments, ensuring flexibility in application. Primary Value and User Solutions: Supervisely AI addresses the challenges of developing and deploying computer vision applications by providing an all-in-one platform that simplifies data annotation, model training, and team collaboration. It reduces the time and effort required to build high-quality AI models, thereby accelerating the development process and enabling organizations to implement AI solutions more efficiently.

#### Who Is the Company Behind Supervisely AI?

- **Seller:** [Supervisely AI](https://www.g2.com/sellers/supervisely-ai)
- **Year Founded:** 2013
- **HQ Location:** San Francisco, US
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=b9a5e5ad7820e2bb98036db308d18f439d935a946cb053ab04cbb8196158c375&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F10456352&secure%5Burl_type%5D=linkedin_company_website)  
2 employees on LinkedIn®

### [Tagi5](https://www.g2.com/products/tagi5/reviews)

#### Who Is the Company Behind Tagi5?

- **Seller:** [Tagi5](https://www.g2.com/sellers/tagi5)
- **Year Founded:** 2026
- **HQ Location:** N/A
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=df500f773dbde64db8970da182ba8210ffa35abe667d52f18d221419893a53e6&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Ftagi5&secure%5Burl_type%5D=linkedin_company_website)  
1 employees on LinkedIn®

### [Tagi5 AI](https://www.g2.com/products/tagi5-ai/reviews)

Tagi5 is an AI-powered annotation and labeling platform designed to streamline the creation of high-quality training datasets for machine learning and artificial intelligence applications. By unifying image, document, and video labeling into a single intelligent workspace, Tagi5 enhances speed, precision, and governance for data teams of all sizes. It supports various annotation types, including bounding boxes, polygons, OCR extraction, masking, and key-value tagging, ensuring comprehensive coverage for diverse data annotation needs. Key Features and Functionality: - Unified Annotation Workspace: Seamlessly annotate images, documents, and videos within a consistent interface, eliminating the need for multiple tools. - Versatile Annotation Tools: Utilize a range of annotation types such as bounding boxes, polygons, OCR/text extraction, entity labeling, key-value extraction, and masking to cater to various project requirements. - Advanced Visual Controls: Enhance accuracy with in-tool editing, hover highlights, and consistent label color coding. - Productivity Accelerators: Increase efficiency through features like copy-to-next, auto-save, keyboard shortcuts, and rapid navigation. - Built-In Quality Assurance: Maintain dataset reliability with integrated approval workflows, annotation history tracking, and detailed change logs. - Flexible Export Options: Support batch exports in formats like COCO, YOLO, JSON, and XML, complete with metadata for seamless integration into machine learning pipelines. - Role-Based Access Control: Implement granular permissions, role-specific dashboards, and task assignments to manage team collaboration effectively. - Enterprise-Grade Performance: Choose from SaaS, on-premise, and hybrid deployment options, all designed to handle high concurrency and scalability. - Integration and Extensibility: Connect with MLOps pipelines, leverage AI-assisted labeling, and automate workflows to fit into existing operational frameworks. Primary Value and User Solutions: Tagi5 addresses the challenges faced by data teams in producing reliable training datasets amidst the growing complexity of AI systems. By consolidating annotation tools into a unified platform, it eliminates fragmentation and accelerates labeling workflows. The platform's built-in governance and quality assurance mechanisms ensure data accuracy and compliance, reducing the risk of errors and rework. With scalable infrastructure and productivity-enhancing features, Tagi5 empowers organizations to develop AI models more efficiently, ultimately leading to faster deployment and improved performance of AI applications.

#### Who Is the Company Behind Tagi5 AI?

- **Seller:** [Tagi5 AI](https://www.g2.com/sellers/tagi5-ai)
- **Year Founded:** 2026
- **HQ Location:** N/A
- **LinkedIn® Page:** [linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=ea90ace3ce83a2ac10c77a6c50b604eca88bcd61623901b5ad62d6487b6dea08&secure%5Burl%5D=https%3A%2F%2Flinkedin.com%2Fcompany%2Ftagi5&secure%5Burl_type%5D=linkedin_company_website)  
1 employees on LinkedIn®

### [Talp.ai](https://www.g2.com/products/talp-ai/reviews)

Talp simulates and predicts human behavior and intent for companies and organizations.

#### Who Is the Company Behind Talp.ai?

- **Seller:** [talp](https://www.g2.com/sellers/talp)
- **HQ Location:** San Francisco, US
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=69c096f14befee906efb436cdd79e1f74eb9c6172ded76b2304b17213586d53e&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fgettalp&secure%5Burl_type%5D=linkedin_company_website)  
11 employees on LinkedIn®

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[Browse Data Labeling Themes](/categories/data-labeling/themes)

 ![Bijou Barry](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Bijou Barry")
BB

Researched and written by [Bijou Barry](https://research.g2.com/insights/author/bijou-barry)

Updated April 9, 2026

Data labeling software helps data science and machine learning teams source, manage, annotate, and classify unstructured data, including text, images, videos, audio, and PDFs, into labeled datasets that create efficient training data pipelines for building and improving AI and ML models.

### Core Capabilities of Data Labeling Software

To qualify for inclusion in the Data Labeling category, a product must:

- Integrate a managed workforce and/or data labeling service
- Ensure labels are accurate and consistent
- Give the user the ability to view analytics that monitor the accuracy and speed of labeling
- Allow annotated data to be integrated into data science and machine learning platforms to build machine learning models

### Common Use Cases for Data Labeling Software

ML engineers, data scientists, and AI teams use data labeling tools to build high-quality training datasets across a wide range of application types. Common use cases include:

- Annotating images, video, and text for computer vision, NLP, and speech recognition model training
- Fine-tuning and evaluating large language models (LLMs) with human-labeled feedback data
- Building training pipelines for object detection, named entity recognition, and sentiment analysis applications

### How Data Labeling Software Differs from Other Tools

Data labeling is a foundational building block of the AI development lifecycle, distinct from the downstream tools it feeds. It integrates with [generative AI software](https://www.g2.com/categories/generative-ai), [MLOps platforms](https://www.g2.com/categories/mlops-platforms), [data science and machine learning platforms](https://www.g2.com/categories/data-science-and-machine-learning-platforms), [LLM software](https://www.g2.com/categories/large-language-models-llms), and [active learning tools](https://www.g2.com/categories/active-learning-tools) to support the full model development pipeline.

### Insights from G2 on Data Labeling Software

Based on category trends on G2, labeling accuracy controls and workforce management features stand out as standout capabilities. Faster training data pipeline construction and improved model accuracy stand out as primary outcomes of adoption.

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