Best Data Labeling Software in Mexico

Use AI to Train AI Better - Pixel Accurate Tools for Annotation - Annotator Performance Management - Labeling Instruction Builder - Data Security & Privacy Controls

Lodestar is a complete solution for creating computer vision models from video data. The world's first active learning data annotation platform allows you to label hours of video and speed up the creation of high-quality datasets and computer vision models. Automated data preparation makes it easy to drag and drop 10 hours worth of video into one project. Multiple video formats are supported and no data curation is required. Annotators and data scientists can collaborate to create a functional object detection model within an hour by using continuous model training and a shared managed dataset. Every plan comes with unlimited labels.

UBIAI's powerful labeling platform makes it easy to quickly train and deploy your NLP model. To train a high-performance model, it is important to preserve the layout of semi-structured text like invoices and contracts. UBIAI's OCR function combines natural language processing with computer vision. It allows you to perform NER and relation extraction on native PDF documents. You can also scan images or photos from your phone and perform classification annotation. This will significantly improve your NLP model performance. UBIAI's text annotation tool allows you to perform named entity recognition (NER), document classification, and relation extraction all from one interface. UBIAI allows you to create multiple relations in nested or overlapping entities, unlike other tools.

Atlas integrates with your workflow by organizing text, embedding datasets and creating interactive maps that can be explored in a web browser. To understand your data, you don't need to scroll through Excel files or log Dataframes. Atlas automatically analyzes, organizes, and summarizes your documents, surfacing patterns and trends. Atlas' pre-organized data interface makes it easy to quickly identify and remove any data that could be harmful to your AI projects. You can label and tag your data, while cleaning it up with instant sync to your Jupyter notebook. Although vector databases are powerful, they can be difficult to interpret. Atlas stores, visualizes, and allows you to search through all your vectors within the same API.

CVAT, the leading data engine for machine-learning, allows you to annotate better. Teams at all scales use and trust CVAT for data of all sizes. CVAT's intuitive, lightning-fast user interface was developed in collaboration with real-world teams that are solving real-world issues. CVAT is used by the most ambitious AI teams in the world every day, from medical to retail to autonomous cars. CVAT can handle any input data and expected results. It works well with images, videos and even 3D. Bounding boxes and polygons. Points, skeletons. Cuboids. Trajectories. Automated interactive algorithms such as intelligent scissors, histogram equality, and others will help you annotate more efficiently. Get actionable insights from metrics such as the annotator's working hours, the number of objects per hour and more.

Support for various types of annotations, both on images and videos. Open-source, scalable web annotation tool. Support for simple "click and dragging" actions, and options to add more attributes. Features include the ability to copy boundaries and fit boundaries using Bezier curves. Mark the area where the driver is driving. Annotate lane markings for vision-based vehicle location and trajectory planning. Four-click method that is intuitive and accurate to encapsulate the objects of interest. Predict annotations using object tracking algorithm and interpolation algorithm to bounding boxes. Annotation prediction for object instances. Tracking features for 2D objects are now available in 3D.

Curate the most valuable unlabeled datasets to maximize domain coverage and improve models. Register your metadata with Dioptra and your data will stay with you. A data-centric toolkit can help you identify the root cause of model failures and regressions. Active learning miners allow you to sample the most valuable unlabeled datasets. Use Dioptra APIs to integrate your labeling and training stack. Curate data at scale and systematically for your use case. Open source data curation and management for computer vision (including NLP), LLMs, and NLP. We helped our customers improve the accuracy of their models on hard cases, reduce their training cycles, as well as reduce labeling costs.

Accelerate the entire machine learning lifecycle. Developers and data scientists can have more productive experiences building, training, and deploying machine-learning models faster by empowering them. Accelerate time-to-market and foster collaboration with industry-leading MLOps -DevOps machine learning. Innovate on a trusted platform that is secure and trustworthy, which is designed for responsible ML. Productivity for all levels, code-first and drag and drop designer, and automated machine-learning. Robust MLOps capabilities integrate with existing DevOps processes to help manage the entire ML lifecycle. Responsible ML capabilities – understand models with interpretability, fairness, and protect data with differential privacy, confidential computing, as well as control the ML cycle with datasheets and audit trials. Open-source languages and frameworks supported by the best in class, including MLflow and Kubeflow, ONNX and PyTorch. TensorFlow and Python are also supported.

The best platform for the entire lifecycle of computer vision. You can go from image annotation to precise neural networks in 10x less time. Our best-in-class data labeling software transforms images, videos, and 3D point clouds into high-quality training data. You can train your models, track experiments and visualize the results. Our self-hosted solution guarantees data privacy, powerful customization capabilities and easy integration into any technology stack. Computer Vision is a turnkey solution: multi-format data management, quality control at scale, and neural network training in an end-to-end platform. Professional video editing software created by data scientists for data science -- the most powerful tool for machine learning and other purposes.

Our fully managed solution makes it easy to create training datasets for computer-vision models. Data labeling is a key factor in creating effective deep learning models. We aim to be the industry's most trusted data labeling platform, helping companies fully take advantage of AI's potential. You can organize your media using discrete categories. You can identify items of interest using one or more bounding boxes. Similar to bounding boxes but with more precision. You can annotate objects with precise width, depth, height. Each pixel in an image should be classified. Each point in an image should be marked. Annotate straight lines within an image. Measure, yaw and pitch the item of interest. Annotate timestamps in audio and video content. Annotate lines that are not defined in an image.

Our cloud-based annotating platform allows you to create and track projects, annotate, track progress, and download annotation results. You can assign your tasks to either our managed annotation team, or to our global crowd.

Image classification, bounding boxes, polygons, curves, 3D localization Video trace. Text classification, text entity labeling. You can create your own label tool with the support of a custom task plugin. Export PascalVoc XML (The same format as CoreNLP and ImageNet). Supports Windows/Mac/CentOS/Ubuntu.

Appen combines the intelligence of over one million people around the world with cutting-edge algorithms to create the best training data for your ML projects. Upload your data to our platform, and we will provide all the annotations and labels necessary to create ground truth for your models. An accurate annotation of data is essential for any AI/ML model to be trained. This is how your model will make the right judgments. Our platform combines human intelligence with cutting-edge models to annotation all types of raw data. This includes text, video, images, audio and video. It creates the exact ground truth for your models. Our user interface is easy to use, and you can also programmatically via our API.

Manage unstructured data to develop AI solutions in record time. Enterprise-grade data platform with vision AI. Dataloop offers a single-stop-shop for building and deploying powerful data pipelines for computer vision, data labeling, automation of data operations, customizing production pipelines, and weaving in the human for data validation. Our vision is to make machine-learning-based systems affordable, scalable and accessible for everyone. Explore and analyze large quantities of unstructured information from diverse sources. Use automated preprocessing to find similar data and identify the data you require. Curate, version, cleanse, and route data to where it's required to create exceptional AI apps.

Your A.I. can be created using the Edgecase Platform In less than one day, your A.I. team can create 100k labeled photos -Data accuracy is guaranteed to be perfect because it is generated from 3D models and real life blended imagery. Data accuracy is no longer a concern -Each model can be modified, including the camera angle. You can change lighting, textures, camera angles, scene types, and more. All accessible via the cloud - Your A.I. Your existing data can be used to create your own datasets. We also have a large library of 3d hyper-realistic models that you can use to create your own.

Our proprietary labeling platform allows us to label your data with higher quality standards in order to meet the requirements of complex AI projects. Now you can create the products that your customers love.

Data cleaning and labeling are simplified with easy integration. You can deploy and monitor AI applications on your existing platforms. Start with your target business ROI. Then, define quality, cost and speed priorities. Super.AI will deliver the results. You can use any combination of AI, human, and RPA software bots. Mix and match AI models from Amazon and Google. First-generation IDP solutions used basic AI technologies that required extensive setup, post-processing and exception handling. Super.AI IDP, a next-generation solution, is built on top a unified AI platform. It can process any type of document or unstructured data, leverages the most recent AI for the best results and guarantees outcomes. A data processing crowd that is available on demand accelerates automation while reducing cost and complexity. The platform automatically determines the best combination of AI, humans, and bot workers to ensure results. Users can then make trade-offs between speed, quality, and cost.

Superb AI offers a new generation of machine learning data platform to AI team members so they can create better AI in a shorter time. The Superb AI Suite, an enterprise SaaS platform, was created to aid ML engineers, product teams and data annotators in creating efficient training data workflows that save time and money. Superb AI can help ML teams save more than 50% on managing training data. Our customers have averaged a 80% reduction in the time it takes for models to be trained. Fully managed workforce, powerful labeling and training data quality control tools, pre-trained models predictions, advanced auto-labeling and filtering your datasets, data source and integration, robust developer tools, ML work flow integrations and many other benefits. Superb AI makes it easier to manage your training data. Superb AI provides enterprise-level features to every layer of an ML organization.

Innotescus is an image and video annotation platform that enables collaboration and data handling. It streamlines Computer Vision development through intuitive collaboration features, smart annotation tools and seamless data handling. Its data visualization tools and cross functional collaboration features help to identify data bias early and improve data accuracy. This allows for faster and more cost-efficient deployments of high-performance Artificial Intelligence.

Upload your data to our cloud and create labeling tasks. Once you are ready, send your tasks to our network medical experts. We can achieve an accuracy level that is superior to any individual board-certified doctor by aggregating multiple opinions. We only reward the best performers. Our medical experts put 100% effort into every case they see, ensuring quality and cost savings. Our medical experts produce tens of thousands per day.

Toloka AI was founded in 2014 after years spent research and experimentation. It is an open platform for collecting data and annotating it. There are over 20 000+ active monthly performers in over 100+ countries. They speak 40+ languages and generate approximately 80 million data annotations each week. Toloka is used by R&D, banking and autonomous vehicles as well as other organizations to generate machine-learning data at scale. It also harnesses the wisdom of the crowd from all over the globe. Gartner ranked Toloka as one of the most notable data labeling solutions in the market in its Hype Cycle for Data Science & ML report.

We offer the highest quality SLA (>95%) even for the most complicated workflows. Our team can assist with everything from the implementation of a solid quality rubric to raising edge case. We are an ethical AI company that has provided economic opportunities to over 52,000 people in underserved and marginalized areas. ML Assisted annotation allowed for efficiency improvements of up to 3-4x per class annotation. We are able to quickly adapt to ramp-ups and focus shifts. Secure work environments are ensured by ISO-certified delivery centers, biometric authentication, 2FA user authentication, and ISO-certified delivery centers. You can quickly re-prioritize tasks, give quality feedback, and monitor production models. All data types are supported. You can do more with less. We combine machine learning with humans to filter data and select images that are relevant to your use cases. Based on your initial guidelines, you will receive sample results. We will work with you to identify and recommend best annotation practices.

Amazon SageMaker lets you identify raw data, such as images, text files and videos. You can also add descriptive labels to generate synthetic data and create high-quality training data sets to support your machine learning (ML). SageMaker has two options: Amazon SageMaker Ground Truth Plus or Amazon SageMaker Ground Truth. These options allow you to either use an expert workforce or create and manage your data labeling workflows. data labeling. SageMaker GroundTruth allows you to manage and create your data labeling workflows. SageMaker Ground Truth, a data labeling tool, makes data labeling simple. It also allows you to use human annotators via Amazon Mechanical Turk or third-party providers.

Data labeling project management is made easier with the fastest data annotation tool. High level of collaboration and automation.

The most flexible data annotation software. Quickly installable. Create custom UIs, or use pre-built labeling template. Layouts and templates that can be customized to fit your dataset and workflow. Detect objects in images. Supported are boxes, polygons and key points. Partition an image into multiple segments. Use ML models to optimize and pre-label the process. Webhooks, Python SDK and API allow you authenticate, create tasks, import projects, manage model predictions and more. ML backend integration allows you to save time by using predictions as a tool for your labeling process. Connect to cloud object storage directly and label data there with S3 and GCP. Data Manager allows you to manage and prepare your datasets using advanced filters. Support multiple projects, use-cases, and data types on one platform. You can preview the labeling interface as you type in the configuration. You can see live serialization updates at the bottom of the page.