Why AI Is the Mother of All Unicorns

With increasing reliance on computer vision (CV) systems in multiple industrial domains, the demand for robust data annotation solutions is rising exponentially. The most recent reports project the data annotation tools market to have a compound annual growth rate (CAGR) of 21.8% from 2024 to 2032. However, as several companies emerge offering annotation platforms and services, finding a cost-effective provider is challenging. While many platforms offer advanced annotation features, only a few meet the scalability and security requirements essential for enterprise-level CV applications. This article discusses the ten best video and image annotation companies in 2024 to help you with your search. The following lists the companies we think are driving the data annotation space: Encord iMerit Appen Label Your Data KeyMakr TrainingData SuperbAI Kili Technology Telus International SuperAnnotate CogitoTech LabelBox Top 12 Data Annotation and Data Labeling Companies Data annotation companies offering labeling solutions must meet stringent security and scalability requirements to match the high standards of the modern artificial intelligence (AI) space. Below are the twelve top companies, ranked based on the following factors:  Data security protocols: Compliance with data security regulations and use of encryption algorithms. Scalability: The solution’s ability to handle large data volumes and variety. Collaboration: Tools allowing different team members to collaborate on projects. Ease of use: A user-friendly interface that is intuitive and easy to navigate. Supported data types: support for different modalities such as video, image, audio, and text. Automation: AI-based labeling for speeding up annotation processes. Other functionalities for streamlining the annotation workflow include integration with cloud services and advanced annotation methods for complex scenarios. Let’s explore each company's annotation platforms or services and see the key features based on the above factors to help you determine the most suitable option. Encord Encord is an end-to-end data platform that enables you to annotate, curate, and manage computer vision datasets through AI-assisted annotation features. It also provides intuitive dashboards to view insights on key metrics, such as label quality and annotator performance, to optimize workforce efficiency and ensure you build production-ready models faster. SOTA Model-assisted Labeling and Customizable Workflows with Encord Annotate Key Features Data security: Encord complies with the General Data Protection Regulation (GDPR), System and Organization Controls 2 (SOC 2), and Health Insurance Portability and Accountability Act (HIPAA) standards. It uses advanced encryption protocols to ensure data security and privacy. Scalability: The platform allows you to upload up to 500,000 images (recommended), 100 GB in size, and 5 million labels per project. You can also upload up to 200,000 frames per video (2 hours at 30 frames per second) for each project. See more guidelines for scalability in the documentation. Collaboration: You can create workflows and assign roles to relevant team members to manage tasks at different stages. User roles include admin, team member, reviewer, and annotator. Ease-of-use: Encord Annotate offers an intuitive user interface (UI) and an SDK to label and manage annotation projects. Supported data types: The platform lets you annotate images, videos (and image sequences), DICOM, and Mammography data. Supported annotation methods: Encord supports multiple annotation methods, including classification, bounding box, keypoint, polylines, and polygons. Automated labeling: The platform speeds up the annotation with automation features, including: - Segment Anything Model (SAM) to automatically create labels around distinct features in all supported file formats. - Interpolation to auto-create instance labels by estimating where labels should be created in videos and image sequences. - Object tracking to follow entities within images based on pixel information enclosed within the label boundary. Integration: Integrate popular cloud storage platforms, such as AWS, Google Cloud, Azure, and Open Telekom Cloud OSS, to import datasets. Best for Teams looking for an enterprise-grade image and video annotation solution to produce high-quality data for computer vision models. Pricing Encord has a pay-per-user pricing model with Starter, Team, and Enterprise options. Learn more about automated data annotation by reading our guide to automated data annotation. iMerit iMerit offers Ango Hub, a data annotation solution built on a generative AI framework that lets you build use-case-specific applications for autonomous vehicles, agriculture, and healthcare industries. iMerit Key Features Collaboration: The Ango Hub solution lets you add labelers and reviewers to customized workflows for managing annotation projects. Ease-of-use: The platform offers an intuitive UI to label items, requiring no coding expertise. Supported data types: Ango Hub supports audio, image, video, DICOM, text, and markdown data types. Supported labeling methods: The solution supports bounding boxes, polygons, polylines, segmentation, and tools for natural language processing (NLP). Integration: The platform features integrated plugins for automated labeling and machine learning models for AI-assisted annotations. Best for Teams searching for an integrated labeling platform for annotating text, video, and image data. Pricing Pricing information is not publicly available. Contact the team to get a quote. Appen Appen offers data annotation solutions for building large language models (LLMs) by providing a standalone labeling platform and data labeling services through expert linguists. Appen Key Features Workforce capacity: Appen’s managed services include more than a million specialists speaking over 200 languages across 170 countries. With the option to combine its platform with its services, the solution becomes highly scalable. Supported data types: Appen’s platform lets you label documents, images, videos, audio, text, and point-cloud data. Supported annotation methods: Labeling methods include bounding boxes, cuboids, lines, points, polygons, ellipses, segmentation, and classification. Instruction datasets: The company also offers domain-specific instruction datasets for training LLMs. Best for Teams looking for a hybrid solution for building multi-modal models for text and vision applications. Pricing Pricing is not publicly available. Label Your Data Label Your Data is a data annotation service provider offering video and image annotation services for CV and NLP applications. Label Your Data Key Features Data security: The company complies with ISO 27001, GDPR, and CCPA standards. Workforce capacity: Label Your Data builds a remote team of over 500 data annotators to speed up the annotation process. Supported data types: The solution supports image, video, point-cloud, text, and audio data. Supported labeling methods: CV methods include semantic segmentation, bounding boxes, polygons, cuboids, and key points. NLP methods include named entity recognition (NER), sentiment analysis, audio transcription, and text annotation. Best for Teams looking for a secure annotation service provider for completely outsourcing their labeling efforts. Pricing Label Your Data provides on-demand, short- and long-term plans. Keymakr Keymakr is an image and video annotation service provider that manages labeling processes through its in-house professional experts. Keymakr Key Features Labeling capacity: You can label up to 100,000 data items. Supported data types: The platform supports image, video, and point-cloud data. Supported labeling methods: Keymakr offers annotations that include bounding boxes, cuboids, polygons, semantic segmentation, key points, bitmasks, and instance segmentation. Smart assignment: The solution features a smart distribution to match relevant annotators with suitable tasks based on skillset. Performance tracking: Keymakr provides performance analytics to track progress and alert managers in case of issues. Data collection and creation: The company also offers services to create relevant data for your projects or collect it from reliable sources. Best for Beginner-level teams working CV projects, requiring data creation and annotation services. Pricing Pricing is not publicly available. TrainingData TrainingData is a Software-as-a-Service (SaaS) data labeling application for CV projects, featuring pixel-level annotation tools for accurate labeling. TrainingData Key Features Data security: The company provides a Docker image to run on your local network through a secure virtual private network (VPN) connection. Scalability: You can label up to 100,000 images. Collaboration: TrainingData’s platform lets you create projects and add relevant collaborators with suitable roles, including reviewer, annotator, and admin. Supported labeling methods: The platform offers multiple labeling tools, including a brush and eraser for pixel-accurate segmentation, bounding boxes, polygons, key points, and a freehand drawer for freeform contours. Integration: TrainingData integrates with any cloud storage service that complies with cross-origin resource sharing (CORS) policy. Best for Teams looking for an on-premises image annotation platform for segmentation tasks. Pricing TrainingData offers free, pro, and enterprise packages. SuperbAI SuperbAI offers multiple products for building AI models, including a data management platform, a labeling solution, and a tool for training, evaluating, and deploying models. SuperbAI Key Features Data security: SuperbAI complies with SOC standards and encrypts all data using Advanced Encryption Standard - 256 (AES-256). Collaboration: The platform offers access management tools and lets you invite team members as admins, labelers, and managers. Supported data types: SuperbAI supports images and videos in PNG, BMP, JPG, and MP4 formats. It also supports point-cloud data. Supported labeling methods: The solution supports all standard labeling methods, including bounding boxes, polylines, polygons, and cuboids. Integration: The platform integrates with Google Cloud, Azure, AWS, and Slack. Best for Teams looking for an integrated data management solution for training machine learning algorithms. Pricing SuperbAI offers starter and enterprise packages. Kili Technology Kili Technology offers an intuitive labeling platform to annotate data for LLMs, generative AI, and CV models with quality assurance features to produce error-free datasets. Kili Technology Key features Collaboration: The platform lets you assign multiple roles to team members, including reviewer, admin, manager, and labeler, to collaborate on projects through instructions and feedback. Ease-of-use: Kili offers a user-friendly UI for managing workflows, requiring minimal code. Supported labeling methods: The tool supports bounding boxes, optical character recognition (OCR), NERs, pose estimation, and semantic segmentation. Automation: Kili supports automated labeling through active learning and pre-annotations using ChatGPT and SAM. Best for Data scientists looking for a lightweight annotation solution for building generative AI applications. Pricing Pricing depends on the number of items you need to label. Telus International Telus International’s Ground Truth (GT) studio offers three platforms as part of a managed service to build training datasets for ML models. GT Manage helps with people and project management; GT Annotate lets you annotate image and video data. GT Data is a data creation and collection tool supporting multiple data types. Telus International Key Features Data security: GT Annotate complies with SOC 2 standards and implements two-factor authentication with firewall applications and intrusion detection for data security. Collaboration: GT Manage features workforce management tools for optimal task distribution and quality control. Supported data types: You can collect image, video, audio, text, and geo-location data using GT data. Supported labeling methods: GT Annotate supports bounding boxes, cuboids, polylines, and landmarks. Best for Teams looking for a complete AI solution for collecting, labeling, and managing raw data. Pricing Pricing information is not publicly available. SuperAnnotate SuperAnnotate offers a data labeling tool that lets you manage AI data through collaboration tools and annotation workflows while providing quality assurance features to produce labeling accuracy. SuperAnnotate Key Features Collaboration: SuperAnnotate lets you create teams and assign relevant roles such as admin, annotator, and reviewer. Ease-of-use: The platform has an easy-to-use UI. Supported data types: SuperAnnotate supports image, video, text, and audio data. Supported labeling methods: The platform has tools for categorization, segmentation, pose estimation, object tracking, sentiment analysis, and speech recognition. Best for Teams looking for an annotation solution to build generative AI applications. Pricing The platform offers free, pro, and enterprise versions. Cogito Cogito is a data labeling service provider that employs a large pool of human annotators to deliver annotations for generative AI, CV, content moderation, NLP, and data processing. Cognito Key Features Data security: Cogito complies with GDPR, SOC 2, HIPAA, CCPA, and ISO 27001 standards. Supported data types: The platform supports image, video, audio, text, and point-cloud data. Automation: Cogito uses AI-based algorithms to label large data volumes. Best for Startups looking for a company to outsource their AI operations. Pricing Pricing is not publicly available. Labelbox Labelbox offers multiple products for managing AI projects. Its data labeling platform allows you to annotate various data types for building vision and LLM applications. LabelBox Key Features Data security: Labelbox complies with several regulatory standards, including GDPR, CCPA, SOC 2, and ISO 27001. Collaboration: Users can create projects and invite in-house labeling team members with relevant roles to manage the annotation workflow. Ease-of-use: Labelbox has a user-friendly interface with a customizable labeling editor. Automation: The platform supports model-assisted labeling (MAL) to import AI-based classifications for your data. Integrability: Labelbox integrates with AWS, Azure, and Google Cloud to access data repositories quickly. Best for Teams looking for labeling solutions to build applications for e-commerce, healthcare, and financial services industries. Pricing Labelbox offers free, starter, and enterprise versions. Still confused about whether to buy a tool or go for open-source solutions? Read some lessons from practitioners regarding build vs. buy decisions Data Annotation Companies: Key Takeaways CV applications are driving the current industrial landscape by innovating fields like medical imaging, robotics, retail, etc. However, CV’s rapid expansion into these domains calls for robust data annotation tools and services to build high-quality training data. Below are a few key points regarding data annotation companies in 2024. Security is key: With data privacy regulations becoming stricter globally, companies offering annotation solutions must have compliance certifications to ensure data protection. Scalability: Annotation companies should offer scalable tools to handle the ever-increasing data volume and variety. Top annotation companies in 2024: SuperAnnotate, Encord, and Kili are the top 3 companies that provide robust labeling platforms and services.

We sat down with Denis Gavrielov, Full Stack Engineer at Encord, to learn more about his day-to-day. Denis is an essential player on the Engineering team, he has been a part of Encord's exciting journey from a small 8-person team to the dynamic startup it is today. He walks us through the highs and lows of his experiences, the camaraderie he shares with his team, and the thrill of working on some truly fascinating projects. If you've ever wondered what it's like to work at a startup like Encord, strap in and join us for this conversation! Denis, first question. What inspired you to join Encord? I applied about two years ago when the team was still getting started (we were eight people strong — all engineers!). At that time, I wasn't sure if I wanted to join a startup as I had been working in a larger company up until then (Bloomberg). I met most of the team throughout the interview process, and the more I spoke to everyone, the more I felt I'd really enjoy working with them. I also had a great first impression of the founders (Eric & Ulrik) and the more I spoke with them the more I got a sense for how strong their skillset was and how unique and unparalleled of an opportunity it'd be. The combination of team, founders, and opportunity is what ultimately led me to join Encord. I still remember my first week sitting in our 10m2 office space in the middle of Soho without any meeting rooms or kitchen, quite different from today! Very different from now indeed! What does a typical day as a full-stack engineer at Encord look like? Every day is a bit different. Some people like to focus on back-end engineering and some like front-end work — I like to work on both! Typically, I start by catching up with everyone's messages on Slack. I might have one or two meetings in the morning before starting to code. Throughout the day there's a lot of collaboration via impromptu short catch-ups in person or on Slack. During these meetings, I often discuss architectural designs and problem-solving strategies with more senior team members. A significant component of my day is spent coding and solving problems. And I guess you fit in lunch in between that as well, right? That's true, a good lunch break is important for recharging! I usually grab lunch with a few colleagues — if the weather is nice, like during the summer, we enjoy our lunch outside. On Fridays, the entire team gets together in the office for a company lunch, that's always fun and one of my favorite Encord traditions. You mentioned teamwork and customer centricity — how would you describe the company culture at Encord more broadly? The company culture is very collaborative. The founders and senior managers are encouraging and open to suggestions, so it's easy to take (good) decisions independently. We try to maintain a relaxed office culture focused on team success, where people are free to work in a manner that works best for them and for us as a team more broadly. People are always trying to help each other out and break down any silos there might arise — although we've been very intentional though about building the right environment, so luckily there are very little silos in the first place. For example, our engineering and commercial team all work in one big room and getting context or feedback is incredibly quick. Another key part of our culture is being able to adapt quickly. Previously, I was working at Bloomberg in an infrastructure team, where we had to plan everything very precisely. Everything had to be correct from the start, and every decision would need to go through many layers of approval and planning sessions. Speed of progress was naturally quite different. Here at Encord, we are a nimble, rapid team — we move quickly and have been able to achieve things that teams many times our size have struggled with. Customers tell us every week how much better our product is compared to other alternatives they're looking at. It is always very rewarding when we hear this feedback. What we aim for as a team is to be great — ship high-performing industry-leading products quickly, get feedback from customers and prospects early, and consistently focus on building what customers and users really want. I think these are the two principles that stand out to me as an engineer the most. Can you tell us a bit about a project that you're currently working on? One of the projects I'm working on is overhauling of our task management system. The core problem we're trying to solve is that our customers need a detailed overview and a flexible interface to control the annotation and review process for their data operations. The process can be complicated, involving multiple review stages and different levels of scrutiny. So we're developing a system to allow our clients to implement more complex workflows and be able to review the process even faster! In terms of how I spend my time between collaborating and individual development, it varies heavily by what point of the project we're in. At the beginning, a large part of my time is spent brainstorming, talking through the objectives with other engineers and product managers, and listening in on client calls. After gathering ideas and refining our approach, I spend most of my time coding and focusing on the project — while still staying in sync with the rest of the team so that we keep moving quickly in the same direction. Lastly, what advice would you give to someone considering working at Encord? Many people reach out to me each week asking this and there's a few things I think many people don't consider. Encord is obviously in a very exciting position — we're a strong team, in the right market (AI infrastructure), and have a clear vision of what the future will be like and what we need to build to get there. Yet early-stage startups, especially ones moving very quickly, require working-modes and dispositions that the vast majority of people are not looking for nor comfortable with — and that's okay! If you don’t particularly enjoy collaborating on tasks, or you prefer being told very precisely/prescriptively what to do, or you're not at the stage in your career where you want to own processes, then I'd say Encord (and similar-type companies) are probably not the best fit. It really depends on what excites you. Here, you need to embrace pace, ownership, collaboration, and autonomy, often to degrees you may not have considered possible. These are key traits that, I think, have all made us successful in our roles. If you want to own problem areas and find solutions, if you like collaborating and prototyping MVPs quickly to get client feedback early, and if you pride yourself in making the right decisions with limited amounts of information — then Encord may be a good fit! Thank you, Denis! We have big plans for 2023 & are hiring across all teams. Find here the roles we are hiring for!

Learn more about life at Encord from our Product Designer, Mavis Lok! Mavis Lok, or ‘Figma Queen’ as we’d like to call her, thrives in using innovation and creativity to enhance the user experience (UX) and user interface (UI) of our products. She listens closely to our customers’ needs, conducts user discovery, and translates insights into tangible and elegant solutions. You will find Mavis collaborating with various teams at Encord (from the Sales and Customer Success teams, to the Product and Engineering teams) to ensure that the product aligns with our business goals and user needs. Hi, Mavis, first question is what inspired you to join Encord? When I was planning the next steps in my career, I knew that I wanted to join an emerging and innovative tech startup. In the process, I stumbled upon Encord - with a pretty big vision of helping companies build better AI models with quality data. A problem that seemed ambitious and compelling.  I had my first chat with Justin [Encord's Head of Product Engineering], and he gave me great insights into the role, the company, and the domain space, which tied nicely with my design experience and what I was looking for in my next role. I was evaluating many companies, and I made sure (and I'd recommend to anyone reading!) to speak to as many employees from the company I could meet. The more people I met from Encord, the more and more eager I became to join the team. Could you tell me a little about what inspired you to pursue a career in product design? Hah, great question! I was previously in creative advertising and was trained as a Creative/Art Director. During my free time, I would participate in advertising competitions where I would pitch ideas for brands, and I’d always maximize my design potential through digital-led ideas. That brought me to work as a Digital Designer and then as a Design Manager, where I got my first glimpse of what it was like to work closely with co-founders, engineers, and designers. The company I was working at, was going through a transition from an agency to a SaaS type business model, and I found many of the skills I'd developed were actually an edge for what product design requires. Having an impact in balancing business needs, and product development challenges whilst creating products that are user-centric and delightful to use - is why I love what I do every day. How would you describe the company culture? I think the people at Encord are what sets us apart. With a team of over 20 nationalities, it’s an incredible feeling to work in an environment where diversity of thought is encouraged.  The grit, ambition, vision, and thoughtfulness of the team are why I enjoy being part of Encord.   What have been some of the highlights of working at Encord? Encord has given me the space to throw light on the impact that design can bring to the company and build more meaningful relationships with the team and, of course, our customers. Another big highlight for me is practicing the notion of coming up with ideas rapidly whilst being able to identify the consequences of every design decision. Brainstorming creativity whilst critically is something I hold dearly in my creative/design life, so it’s definitely a highlight of my day-to-day at Encord. On a side note, Encord is also a fun place to work. Whether it is Friday lunches, monthly social activities, or company off-sites, there are plenty of opportunities to have a good time with the team.  ​​Lastly, what advice would you give someone considering joining Encord? The first thing I would say is you have to be authentic during the interview, and you should also genuinely care about the mission of the company because there is a lot of buzz around the AI space right now - genuine interest lasts longer than hype. I would recommend reading our blogs on the website; it's a great place to start, as you can gain a lot of insight from it. From learning more about our customers, to exploring where our space is headed. We have big plans for 2023 & are hiring across all teams. Find here the roles we are hiring for.