Alternatives to ezML

Ango Hub is an all-in-one, quality-oriented data annotation platform that AI teams can use. Ango Hub is available on-premise and in the cloud. It allows AI teams and their data annotation workforces to quickly and efficiently annotate their data without compromising quality. Ango Hub is the only data annotation platform that focuses on quality. It features features that enhance the quality of your annotations. These include a centralized labeling system, a real time issue system, review workflows and sample label libraries. There is also consensus up to 30 on the same asset. Ango Hub is versatile as well. It supports all data types that your team might require, including image, audio, text and native PDF. There are nearly twenty different labeling tools that you can use to annotate data. Some of these tools are unique to Ango hub, such as rotated bounding box, unlimited conditional questions, label relations and table-based labels for more complicated labeling tasks.

SKY ENGINE AI provides a unified Synthetic Data Cloud designed to power next-generation Vision AI training with photorealistic 3D generative scenes. Its engine simulates multispectral environments—including visible light, thermal, NIR, and UWB—while producing detailed semantic masks, bounding boxes, depth maps, and metadata. The platform features domain processors, GAN-based adaptation, and domain-gap inspection tools to ensure synthetic datasets closely match real-world distributions. Data scientists work efficiently through an integrated coding environment with deep PyTorch/TensorFlow integration and seamless MLOps compatibility. For large-scale production, SKY ENGINE AI offers distributed rendering clusters, cloud instance orchestration, automated randomization, and reusable 3D scene blueprints for automotive, robotics, security, agriculture, and manufacturing. Users can run continuous data iteration cycles to cover edge cases, detect model blind spots, and refine training sets in minutes instead of months. With support for CGI standards, physics-based shaders, and multimodal sensor simulation, the platform enables highly customizable Vision AI pipelines. This end-to-end approach reduces operational costs, accelerates development, and delivers consistently high-performance models.

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.

Viso Suite stands out as the only comprehensive platform designed for end-to-end computer vision solutions. It empowers teams to swiftly train, develop, launch, and oversee computer vision applications without the necessity of starting from scratch with code. By utilizing Viso Suite, organizations can create top-tier computer vision and real-time deep learning systems through low-code solutions and automated software infrastructure. Traditional development practices, reliance on various disjointed software tools, and a shortage of skilled engineers can drain an organization's resources, leading to inefficient, underperforming, and costly computer vision systems. With Viso Suite, users can enhance and implement superior computer vision applications more quickly by streamlining and automating the entire lifecycle. Additionally, Viso Suite facilitates the collection of data for computer vision annotation, allowing for automated gathering of high-quality training datasets. It also ensures that data collection is managed securely, while enabling ongoing data collection to continually refine and enhance AI models for better performance.

alwaysAI offers a straightforward and adaptable platform for developers to create, train, and deploy computer vision applications across a diverse range of IoT devices. You can choose from an extensive library of deep learning models or upload your custom models as needed. Our versatile and customizable APIs facilitate the rapid implementation of essential computer vision functionalities. You have the capability to quickly prototype, evaluate, and refine your projects using an array of camera-enabled ARM-32, ARM-64, and x86 devices. Recognize objects in images by their labels or classifications, and identify and count them in real-time video streams. Track the same object through multiple frames, or detect faces and entire bodies within a scene for counting or tracking purposes. You can also outline and define boundaries around distinct objects, differentiate essential elements in an image from the background, and assess human poses, fall incidents, and emotional expressions. Utilize our model training toolkit to develop an object detection model aimed at recognizing virtually any object, allowing you to create a model specifically designed for your unique requirements. With these powerful tools at your disposal, you can revolutionize the way you approach computer vision projects.

Discover the exciting realm of AI and Machine Learning through your smartphone with FieldDay. We've simplified the intricate process of building machine learning models, transforming it into an interactive and enjoyable experience that's as effortless as taking a photograph. With FieldDay, you can design personalized AI applications and seamlessly integrate them into your preferred tools, all from your mobile device. Simply provide FieldDay with examples to learn from, and it will help you create a tailored model that can be incorporated into your projects or applications. You can explore a variety of applications driven by unique FieldDay machine learning models. Our extensive range of integration options and export capabilities makes it easy to embed a machine learning model into the platform of your choice. FieldDay also enables you to gather data directly using your phone's camera, while our user-friendly interface allows for straightforward and intuitive annotation during data collection, enabling you to build a custom dataset rapidly. Moreover, FieldDay provides the ability to preview and make adjustments to your models in real-time, ensuring an efficient and effective development process. This innovative tool empowers users to harness the power of AI like never before.

Tasq.ai offers an innovative no-code platform designed for creating hybrid AI workflows that merge advanced machine learning techniques with the expertise of decentralized human contributors, which guarantees exceptional scalability, precision, and control. Teams can visually design AI pipelines by disaggregating tasks into smaller micro-workflows that integrate automated inference alongside verified human assessments. This modular approach accommodates a wide range of applications, including text analysis, computer vision, audio processing, video interpretation, and structured data management, all while incorporating features like rapid deployment, flexible sampling, and consensus-based validation. Essential features encompass the global engagement of meticulously vetted contributors, known as “Tasqers,” ensuring unbiased and highly accurate annotations; sophisticated task routing and judgment synthesis to align with predefined confidence levels; and smooth integration into machine learning operations pipelines through intuitive drag-and-drop functionality. Ultimately, Tasq.ai empowers organizations to harness the full potential of AI by facilitating efficient collaboration between technology and human insight.

Nyckel makes it easy to auto-label images and text using AI. We say ‘easy’ because trying to do classification through complicated AI tools is hard. And confusing. Especially if you don't know machine learning. That’s why Nyckel built a platform that makes image and text classification easy. In just a few minutes, you can train an AI model to identify attributes of any image or text. Our goal is to help anyone spin up an image or text classification model in just minutes, regardless of technical knowledge.

Our dashboard provides an in-depth analysis that allows you to confirm all essential details concerning request submissions to Guardrails AI. Streamline your processes by utilizing our comprehensive library of pre-built validators designed for immediate use. Enhance your workflow with strong validation measures that cater to various scenarios, ensuring adaptability and effectiveness. Empower your projects through a flexible framework that supports the creation, management, and reuse of custom validators, making it easier to address a wide range of innovative applications. This blend of versatility and user-friendliness facilitates seamless integration and application across different projects. By pinpointing errors and verifying outcomes, you can swiftly produce alternative options, ensuring that results consistently align with your expectations for accuracy, precision, and reliability in interactions with LLMs. Additionally, this proactive approach to error management fosters a more efficient development environment.

Redactive's developer platform eliminates the need for developers to acquire specialized data engineering expertise, simplifying the process of creating scalable and secure AI-driven applications for both customer engagement and employee productivity. Designed with the security requirements of enterprises in mind, it enables you to expedite your journey to production. There’s no need to overhaul your permission models simply because you are integrating AI into your organization. Redactive consistently honors the access controls established by your data sources, and our data pipeline is designed to avoid the storage of your final documents, thereby minimizing risks associated with downstream technology providers. With a comprehensive suite of pre-built data connectors and reusable authentication flows, Redactive seamlessly integrates with a continually expanding range of tools, complemented by custom connectors and LDAP/IdP provider integrations, ensuring that you can effectively support your AI initiatives regardless of your existing architecture. This flexibility allows businesses to innovate rapidly while maintaining robust security standards.

Our research initiatives in the open-source realm concentrate on developing innovative middleware and software designed to surround and unify large language models (LLMs), alongside creating high-quality enterprise models aimed at automation, all of which are accessible through Hugging Face. LLMWare offers a well-structured, integrated, and efficient development framework within an open system, serving as a solid groundwork for crafting LLM-based applications tailored for AI Agent workflows, Retrieval Augmented Generation (RAG), and a variety of other applications, while also including essential components that enable developers to begin their projects immediately. The framework has been meticulously constructed from the ground up to address the intricate requirements of data-sensitive enterprise applications. You can either utilize our pre-built specialized LLMs tailored to your sector or opt for a customized solution, where we fine-tune an LLM to meet specific use cases and domains. With a comprehensive AI framework, specialized models, and seamless implementation, we deliver a holistic solution that caters to a broad range of enterprise needs. This ensures that no matter your industry, we have the tools and expertise to support your innovative projects effectively.

Your software can see objects in video and images. A few dozen images can be used to train a computer vision model. This takes less than 24 hours. We support innovators just like you in applying computer vision. Upload files via API or manually, including images, annotations, videos, and audio. There are many annotation formats that we support and it is easy to add training data as you gather it. Roboflow Annotate was designed to make labeling quick and easy. Your team can quickly annotate hundreds upon images in a matter of minutes. You can assess the quality of your data and prepare them for training. Use transformation tools to create new training data. See what configurations result in better model performance. All your experiments can be managed from one central location. You can quickly annotate images right from your browser. Your model can be deployed to the cloud, the edge or the browser. Predict where you need them, in half the time.

NVIDIA AI Enterprise serves as the software backbone of the NVIDIA AI platform, enhancing the data science workflow and facilitating the development and implementation of various AI applications, including generative AI, computer vision, and speech recognition. Featuring over 50 frameworks, a range of pretrained models, and an array of development tools, NVIDIA AI Enterprise aims to propel businesses to the forefront of AI innovation while making the technology accessible to all enterprises. As artificial intelligence and machine learning have become essential components of nearly every organization's competitive strategy, the challenge of managing fragmented infrastructure between cloud services and on-premises data centers has emerged as a significant hurdle. Effective AI implementation necessitates that these environments be treated as a unified platform, rather than isolated computing units, which can lead to inefficiencies and missed opportunities. Consequently, organizations must prioritize strategies that promote integration and collaboration across their technological infrastructures to fully harness AI's potential.

Lightly intelligently identifies the most impactful subset of your data, enhancing model accuracy through iterative improvements by leveraging the finest data for retraining. By minimizing data redundancy and bias while concentrating on edge cases, you can maximize the efficiency of your data. Lightly's algorithms can efficiently handle substantial datasets in under 24 hours. Easily connect Lightly to your existing cloud storage solutions to automate the processing of new data seamlessly. With our API, you can fully automate the data selection workflow. Experience cutting-edge active learning algorithms that combine both active and self-supervised techniques for optimal data selection. By utilizing a blend of model predictions, embeddings, and relevant metadata, you can achieve your ideal data distribution. Gain deeper insights into your data distribution, biases, and edge cases to further refine your model. Additionally, you can manage data curation efforts while monitoring new data for labeling and subsequent model training. Installation is straightforward through a Docker image, and thanks to cloud storage integration, your data remains secure within your infrastructure, ensuring privacy and control. This approach allows for a holistic view of data management, making it easier to adapt to evolving modeling needs.

IronYun Vaidio®, AI Vision Platform, delivers 30+ advanced AI video analysis functions to add an extra layer of superhuman intelligence to existing camera and videos infrastructure. Vaidio integrates with 28 leading video management systems and works with any IP camera. Vaidio AI accelerates the intelligence of real-time, video data, and forensic applications. These applications include intrusion, person and vehicle count, face and license plates recognition, vehicle make, model, loitering and crowding, PPE and weapon, smoke and fire recognition, and more. The Vaidio Platform won ISC West New Product Showcase Awards in the last three years for Commercial Monitoring and Loss Prevention.

RoboRealm is a machine vision software for Windows designed to streamline the vision programming process and facilitate quick prototyping through its advanced modules. With a user-friendly graphical interface that demands little to no coding skills, it is suitable for both hobbyists and professional robotic engineers. The software is versatile, supporting a wide array of image processing modules and being compatible with various camera types, which enhances hardware flexibility. Users benefit from real-time adjustments to parameters, and it comes with a fully supported server API that allows seamless integration with other systems. RoboRealm also supports multiple image sources and provides numerous output options, such as file, web, FTP, and email. Its plugin architecture encourages the creation of custom modules, while a vibrant online community is available for expert support. Furthermore, the platform allows users to easily combine various modules through a straightforward pipeline, enabling customized solutions for tasks like surface defect detection, measurement, and counting among others. This adaptability makes RoboRealm an invaluable tool for anyone looking to implement advanced vision capabilities in their projects.

Ultralytics provides a comprehensive vision-AI platform centered around its renowned YOLO model suite, empowering teams to effortlessly train, validate, and deploy computer-vision models. The platform features an intuitive drag-and-drop interface for dataset management, the option to choose from pre-existing templates or to customize models, and flexibility in exporting to various formats suitable for cloud, edge, or mobile applications. It supports a range of tasks such as object detection, instance segmentation, image classification, pose estimation, and oriented bounding-box detection, ensuring that Ultralytics’ models maintain high accuracy and efficiency, tailored for both embedded systems and extensive inference needs. Additionally, the offering includes Ultralytics HUB, a user-friendly web tool that allows individuals to upload images and videos, train models online, visualize results (even on mobile devices), collaborate with team members, and deploy models effortlessly through an inference API. This seamless integration of tools makes it easier than ever for teams to leverage cutting-edge AI technology in their projects.

Create, design, prototype and deploy custom AI workflows. Enhance customer engagement and team/personal productivity. Create and embed your website in just minutes. Connect your chatbot to your knowledge base. Instantly summarize and answer questions about audio, video, and website files. Create marketing copy, personalized emails, call summaries and graphics at large scale. Save time with a library of prebuilt pipelines, such as those for chatbots or document search. Share your pipelines to help the marketplace grow. Your data will not be stored on model providers' servers due to our zero-day retention policy and secure infrastructure. Our partnership begins with a free diagnostic, where we assess if your organization is AI-ready. We then create a roadmap to create a turnkey solution that fits into your processes.

The LEAP Edge AI Platform presents a comprehensive on-device AI toolchain that allows developers to create edge AI applications, encompassing everything from model selection to inference directly on the device. This platform features a best-model search engine designed to identify the most suitable model based on specific tasks and device limitations, and it offers a collection of pre-trained model bundles that can be easily downloaded. Additionally, it provides fine-tuning resources, including GPU-optimized scripts, enabling customization of models like LFM2 for targeted applications. With support for vision-enabled functionalities across various platforms such as iOS, Android, and laptops, it also includes function-calling capabilities, allowing AI models to engage with external systems through structured outputs. For seamless deployment, LEAP offers an Edge SDK that empowers developers to load and query models locally, mimicking cloud API functionality while remaining completely offline, along with a model bundling service that facilitates the packaging of any compatible model or checkpoint into an optimized bundle for edge deployment. This comprehensive suite of tools ensures that developers have everything they need to build and deploy sophisticated AI applications efficiently and effectively.

Dynamiq serves as a comprehensive platform tailored for engineers and data scientists, enabling them to construct, deploy, evaluate, monitor, and refine Large Language Models for various enterprise applications. Notable characteristics include: 🛠️ Workflows: Utilize a low-code interface to design GenAI workflows that streamline tasks on a large scale. 🧠 Knowledge & RAG: Develop personalized RAG knowledge bases and swiftly implement vector databases. 🤖 Agents Ops: Design specialized LLM agents capable of addressing intricate tasks while linking them to your internal APIs. 📈 Observability: Track all interactions and conduct extensive evaluations of LLM quality. 🦺 Guardrails: Ensure accurate and dependable LLM outputs through pre-existing validators, detection of sensitive information, and safeguards against data breaches. 📻 Fine-tuning: Tailor proprietary LLM models to align with your organization's specific needs and preferences. With these features, Dynamiq empowers users to harness the full potential of language models for innovative solutions.

Qwen2.5-VL marks the latest iteration in the Qwen vision-language model series, showcasing notable improvements compared to its predecessor, Qwen2-VL. This advanced model demonstrates exceptional capabilities in visual comprehension, adept at identifying a diverse range of objects such as text, charts, and various graphical elements within images. Functioning as an interactive visual agent, it can reason and effectively manipulate tools, making it suitable for applications involving both computer and mobile device interactions. Furthermore, Qwen2.5-VL is proficient in analyzing videos that are longer than one hour, enabling it to identify pertinent segments within those videos. The model also excels at accurately locating objects in images by creating bounding boxes or point annotations and supplies well-structured JSON outputs for coordinates and attributes. It provides structured data outputs for documents like scanned invoices, forms, and tables, which is particularly advantageous for industries such as finance and commerce. Offered in both base and instruct configurations across 3B, 7B, and 72B models, Qwen2.5-VL can be found on platforms like Hugging Face and ModelScope, further enhancing its accessibility for developers and researchers alike. This model not only elevates the capabilities of vision-language processing but also sets a new standard for future developments in the field.

Red5 Pro is your ultimate solution for real-time video and audio streaming with ultra-low latency under 250 milliseconds. It can be deployed on-premises or in the cloud. Ideal for developers, startups, SMEs, and enterprises, it supports WebRTC, RTMP, RTSP, HLS, SRT, MPEG-TS, and Zixi protocols, making it a versatile choice across diverse use cases. With Red5 Pro, scalability meets reliability. Cluster your deployment to support millions of concurrent viewers while leveraging autoscaling on your preferred cloud platform. Red5 Pro offers end-to-end encryption and Flexible APIs to customize your setup. This streaming engine also comes with SDKs for iOS, Android, Windows, macOS, Linux, Unity, and Unreal Engine, making integration straightforward and giving you full control over your streaming.

No business desires outdated information when their AI interacts with customers. Neum AI enables organizations to maintain accurate and current context within their AI solutions. By utilizing pre-built connectors for various data sources such as Amazon S3 and Azure Blob Storage, as well as vector stores like Pinecone and Weaviate, you can establish your data pipelines within minutes. Enhance your data pipeline further by transforming and embedding your data using built-in connectors for embedding models such as OpenAI and Replicate, along with serverless functions like Azure Functions and AWS Lambda. Implement role-based access controls to ensure that only authorized personnel can access specific vectors. You also have the flexibility to incorporate your own embedding models, vector stores, and data sources. Don't hesitate to inquire about how you can deploy Neum AI in your own cloud environment for added customization and control. With these capabilities, you can truly optimize your AI applications for the best customer interactions.

Effortlessly create, launch, and oversee computer vision applications with a fully managed application development environment that cuts down the development time from days to mere minutes at a fraction of the cost compared to existing solutions. Seamlessly ingest live video and image streams on a global scale, allowing for rapid and convenient data handling. Utilize a user-friendly drag-and-drop interface to develop computer vision applications with ease. Efficiently store and search through petabytes of data, all while benefiting from integrated AI functionalities. Vertex AI Vision equips users with comprehensive tools to manage every stage of their computer vision application life cycle, including ingestion, analysis, storage, and deployment. Connect the output of your applications effortlessly to data destinations, such as BigQuery for in-depth analytics or live streaming to promptly drive business decisions. Ingest and process thousands of video streams from various locations worldwide, ensuring scalability and flexibility. With a subscription-based pricing model, users can take advantage of costs that are up to ten times lower than those of previous options, providing a more economical solution for businesses. This innovative approach allows organizations to harness the full potential of computer vision technology with unprecedented efficiency and affordability.

The Video Explorer Platform serves as a comprehensive solution for the development and deployment of video analytics applications, leveraging computer vision technology. It features an adaptable application framework that can be tailored to meet specific business needs, facilitating seamless integration with existing customer systems. This platform allows enterprises to implement video analytics solutions swiftly and efficiently. When combined with the IBM Visual Builder (IVB), users gain advantages from a streamlined, single-stop process for developing and deploying video analytics applications, which encompasses tasks such as image labeling, image augmentation, and model training. Additionally, it offers robust features for managing data sources, including video devices, images, and offline video materials, alongside functionalities for real-time video browsing, image extraction, storage solutions, model mapping, and event processing rule configuration. Overall, the Video Explorer Platform is designed to empower businesses with the tools necessary for effective video analytics implementation.

VisionAgent is an innovative application builder for generative Visual AI created by Landing AI, aimed at speeding up the process of developing and implementing vision-capable applications. Users can simply enter a prompt that outlines their vision-related task, and VisionAgent adeptly chooses the most appropriate models from a handpicked assortment of successful open-source options to fulfill that task. It not only generates the necessary code but also tests and deploys it, facilitating the quick creation of applications that encompass object detection, segmentation, tracking, and activity recognition. This efficient methodology enables developers to craft vision-enabled applications within minutes, resulting in a significant reduction in both time and effort required for development. Additionally, the platform enhances productivity by providing instant code generation for tailored post-processing tasks. With VisionAgent, developers can trust that the best model will be selected for their specific requirements from a carefully curated library of the most effective open-source models, ensuring optimal performance for their applications. Ultimately, VisionAgent transforms the way developers approach the creation of visual AI solutions, making advanced technology accessible and practical.

Develop a tailored computer vision model in just a few minutes with AI Custom Vision, a component of Azure AI Services, which allows you to personalize and integrate advanced image analysis for various sectors. Enhance customer interactions, streamline production workflows, boost digital marketing strategies, and more, all without needing any machine learning background. You can configure your model to recognize specific objects relevant to your needs. The user-friendly interface simplifies the creation of your image recognition model. Begin training your computer vision solution by uploading and tagging a handful of images, after which the model will evaluate its performance on this data and improve its accuracy through continuous feedback as you incorporate more images. To facilitate faster development, take advantage of customizable pre-built models tailored for industries such as retail, manufacturing, and food services. For instance, Minsur, one of the largest tin mining companies globally, demonstrates the effective use of AI Custom Vision to promote sustainable mining practices. Additionally, you can trust that your data and trained models are protected by robust enterprise-level security and privacy measures. This ensures confidence in the deployment and management of your innovative computer vision solutions.

Llama Guard is a collaborative open-source safety model created by Meta AI aimed at improving the security of large language models during interactions with humans. It operates as a filtering mechanism for inputs and outputs, categorizing both prompts and replies based on potential safety risks such as toxicity, hate speech, and false information. With training on a meticulously selected dataset, Llama Guard's performance rivals or surpasses that of existing moderation frameworks, including OpenAI's Moderation API and ToxicChat. This model features an instruction-tuned framework that permits developers to tailor its classification system and output styles to cater to specific applications. As a component of Meta's extensive "Purple Llama" project, it integrates both proactive and reactive security measures to ensure the responsible use of generative AI technologies. The availability of the model weights in the public domain invites additional exploration and modifications to address the continually changing landscape of AI safety concerns, fostering innovation and collaboration in the field. This open-access approach not only enhances the community's ability to experiment but also promotes a shared commitment to ethical AI development.

Google AI Edge presents an extensive range of tools and frameworks aimed at simplifying the integration of artificial intelligence into mobile, web, and embedded applications. By facilitating on-device processing, it minimizes latency, supports offline capabilities, and keeps data secure and local. Its cross-platform compatibility ensures that the same AI model can operate smoothly across various embedded systems. Additionally, it boasts multi-framework support, accommodating models developed in JAX, Keras, PyTorch, and TensorFlow. Essential features include low-code APIs through MediaPipe for standard AI tasks, which enable rapid incorporation of generative AI, as well as functionalities for vision, text, and audio processing. Users can visualize their model's evolution through conversion and quantification processes, while also overlaying results to diagnose performance issues. The platform encourages exploration, debugging, and comparison of models in a visual format, allowing for easier identification of critical hotspots. Furthermore, it enables users to view both comparative and numerical performance metrics, enhancing the debugging process and improving overall model optimization. This powerful combination of features positions Google AI Edge as a pivotal resource for developers aiming to leverage AI in their applications.

Cognex VisionPro, the most popular PC-based vision software, is available. It can be used to set up and deploy vision applications regardless of the camera or frame grabber. VisionPro allows users to perform a wide variety of functions, including inspection and location of geometric objects, alignment and measurement, and specialized functions for electronics and semiconductor applications.

The Linker VisionAI Platform offers a holistic, all-in-one solution for vision AI, incorporating elements of simulation, training, and deployment to enhance the capabilities of smart cities and businesses. It is built around three essential components: Mirra, which generates synthetic data through NVIDIA Omniverse and NVIDIA Cosmos; DataVerse, which streamlines data curation, annotation, and model training with NVIDIA NeMo and NVIDIA TAO; and Observ, designed for the deployment of large-scale Vision Language Models (VLM) using NVIDIA NIM. This cohesive strategy facilitates a smooth progression from simulated data to practical application, ensuring that AI models are both resilient and flexible. By utilizing urban camera networks and advanced AI technologies, the Linker VisionAI Platform supports a variety of functions, such as managing traffic, enhancing worker safety, and responding to disasters. In addition, its comprehensive capabilities allow organizations to make well-informed decisions in real-time, significantly improving operational efficiency across diverse sectors.

FiftyOne, developed by Voxel51, stands out as a leading platform for visual AI and computer vision data management. The effectiveness of even the most advanced AI models diminishes without adequate data, which is why FiftyOne empowers machine learning engineers to thoroughly analyze and comprehend their visual datasets, encompassing images, videos, 3D point clouds, geospatial information, and medical records. With a remarkable count of over 2.8 million open source installations and an impressive client roster that includes Walmart, GM, Bosch, Medtronic, and the University of Michigan Health, FiftyOne has become an essential resource for creating robust computer vision systems that function efficiently in real-world scenarios rather than just theoretical environments. FiftyOne enhances the process of visual data organization and model evaluation through its user-friendly workflows, which alleviate the burdensome tasks of visualizing and interpreting insights during the stages of data curation and model improvement, tackling a significant obstacle present in extensive data pipelines that manage billions of samples. The tangible benefits of employing FiftyOne include a notable 30% increase in model accuracy, a savings of over five months in development time, and a 30% rise in overall productivity, highlighting its transformative impact on the field. By leveraging these capabilities, teams can achieve more effective outcomes while minimizing the complexities traditionally associated with data management in machine learning projects.

Enhance your decision-making and responsiveness to events with AI, leveraging your current IP camera setup. Traditionally, cameras serve primarily for security and surveillance; however, we introduce advanced Machine Vision models that transform this everyday tool into a significant asset for your team. Our solutions are designed to enhance operational efficiency for both employees and clients while strictly safeguarding privacy—there's no use of facial recognition or long-term tracking, without exception. By minimizing the number of individuals involved, we eliminate the invasive and unmanageable practice of relying on personnel to sift through footage. Our approach allows you to focus solely on the relevant moments and at the most opportune times. Black.ai integrates a privacy layer that functions between security cameras and operational teams, fostering a superior experience for everyone without compromising their trust. Additionally, Black.ai seamlessly connects with your existing camera systems through parallel streaming protocols, ensuring installation without incurring extra infrastructure expenses or disrupting ongoing operations. In this way, we empower organizations to utilize their surveillance systems to their fullest potential while maintaining the highest standards of privacy.

Flexible Vision is an innovative solution that combines AI-powered machine vision software and hardware, allowing teams to efficiently tackle complex visual inspections. Through its cloud portal, teams can easily collaborate and share vision inspection programs across various factory floors. To get started, gather 5-10 images showcasing both good and defective parts; our software can enhance this dataset with optional augmentation. With just a single click, the creation of your model will commence, and it will be prepared for production within minutes. The deployment of your AI model is automatic, ensuring it is ready for validation promptly. You can download or synchronize the model across multiple on-premises production lines as needed. Our high-speed industrial processors efficiently handle image processing, enabling you to select the desired AI model from a dropdown menu and observe live detections on your screen. Designed for both manual inspection stations and integration into conventional factory automation, our systems are compatible with IO and field-bus protocols, providing versatility for various operational setups. This technology not only streamlines inspection processes but also enhances overall productivity.

Lleverage is used by product and engineering teams to create AI features that are production-ready. Fast. Even if you don't have any prior AI experience. Create comprehensive workflows by using the powerful visual designer, designed to simplify building AI features & pipelines from scratch. Our powerful visual builder simplifies the creation of AI pipelines and features. Use detailed logs to optimize features continuously. Using proprietary datasets, you can fine-tune foundational models to your specific needs and customize them.

Alteia stands out as a premier AI software platform that facilitates digital transformation by harnessing the power of visual data analysis. It addresses essential business requirements across multiple sectors, including predictive maintenance, safety assessments, productivity optimization, and yield forecasting, through its suite of prebuilt, customizable, and valuable AI applications. By integrating computer vision with advanced AI technologies, Alteia ensures that diverse industries have access to a secure, centralized database for all their visual data, enabling the development of innovative and impactful applications. This comprehensive approach not only enhances operational efficiency but also drives significant improvements in decision-making processes across various fields.

Gen App Builder stands out in the realm of generative AI solutions for developers, as it presents an orchestration layer that simplifies the integration of diverse enterprise systems alongside generative AI tools, thereby enhancing the overall user experience. It facilitates a guided orchestration process for search and conversational applications, complete with pre-made workflows for frequently performed actions such as onboarding, data ingestion, and customization, which significantly streamlines app setup and deployment for developers. Utilizing Gen App Builder enables developers to create applications in mere minutes or hours; with the aid of Google’s no-code conversational and search tools that are driven by foundation models, organizations can swiftly initiate projects and construct high-quality user experiences that seamlessly integrate into their platforms and websites. This innovative approach not only accelerates development but also empowers organizations to adapt quickly to changing user needs and preferences in a competitive landscape.

SuperAnnotate is the best platform to build high-quality training datasets for NLP and computer vision. We enable machine learning teams to create highly accurate datasets and successful pipelines of ML faster with advanced tooling, QA, ML, and automation features, data curation and robust SDK, offline accessibility, and integrated annotation services. We have created a unified annotation environment by bringing together professional annotators and our annotation tool. This allows us to provide integrated software and services that will lead to better quality data and more efficient data processing.

Gain a comprehensive understanding of your model's efficacy by logging both inputs and outputs while enhancing them with relevant metadata and user insights. This approach allows you to truly assess your model's functionality and identify areas that require refinement. Keep an eye out for errors and pinpoint underperforming user segments and scenarios that may need attention. The most effective models leverage user-generated data; therefore, systematically collect atypical or low-performing instances to enhance your model through retraining. Rather than sifting through countless outputs following adjustments to your prompts or models, adopt a programmatic evaluation of your LLM-driven applications. Rapidly identify and address performance issues by monitoring new deployments in real-time and effortlessly updating the version of your application that users engage with. Establish connections between your self-hosted or third-party models and your current data repositories for seamless integration. Handle enterprise-scale data effortlessly with our serverless streaming data flow engine, designed for efficiency and scalability. Moreover, Gantry adheres to SOC-2 standards and incorporates robust enterprise-grade authentication features to ensure data security and integrity. This dedication to compliance and security solidifies trust with users while optimizing performance.

Test, launch and refine Gen AI prompting. RAG Agents. Datasets. Workflows. A single workspace for Engineers and Product Managers to explore LLM technology.

Develop your own models, access a variety of pre-trained computer vision frameworks and application templates, and discover how to build AI applications or tackle business challenges using computer vision in just a few hours. Begin by creating a dataset for object detection by uploading images relevant to your training needs, with the capability to include as many as 5,000 images in each dataset. Once you have uploaded the images, they will automatically enter the training process, and you will receive a notification upon the completion of the model training. After this, you can easily download your model for detection purposes. Furthermore, you have the option to integrate your model with our existing application templates, facilitating swift coding solutions. Additionally, our mobile application, compatible with both Android and iOS platforms, harnesses the capabilities of computer vision to assist individuals who are completely blind in navigating daily challenges. This app can alert users to dangerous objects or signs, identify everyday items, recognize text and currency, and interpret basic situations through advanced deep learning techniques, significantly enhancing the quality of life for its users. The integration of such technology not only fosters independence but also empowers those with visual impairments to engage more fully with the world around them.

Capture production data. Evaluate outputs together and fine-tune the performance of your LLM. A detailed log overview will help you understand what is happening in production. Work with domain experts, product managers and engineers to create reliable model outputs. Track AI metrics, such as speed, token usage, and quality scores. Copilot automates model evaluations and improvements for your use cases. Create, manage, or optimize prompts for precise and relevant interactions between AI models and users. Compare fine-tuned models and foundation models to improve prompt performance. Build a fine-tuning dataset with your team. Create custom fine-tuning data to optimize model performance.

Effortlessly deploy all leading machine learning frameworks like Pytorch, Onnx, and XGBoost with a single line of code. If you lack your own models, take advantage of our prebuilt options that are optimized for performance with sub-second latency. You can also fine-tune smaller models for specific tasks, which helps to reduce both costs and latency while enhancing overall performance. With just a few lines of code, you can avoid the hassle of managing infrastructure because we handle that for you. Seamlessly integrate with premier ML observability platforms to receive alerts about any feature or prediction drift, allowing for quick comparisons between model versions and prompt issue resolution. Additionally, you can identify the root causes of prediction and feature drift to tackle any decline in model performance effectively. Gain insights into which features are most influential in driving your model's performance, empowering you to make informed adjustments. This comprehensive approach ensures that your machine learning processes are both efficient and effective.

Xilinx's AI development platform for inference on its hardware includes a suite of optimized intellectual property (IP), tools, libraries, models, and example designs, all crafted to maximize efficiency and user-friendliness. This platform unlocks the capabilities of AI acceleration on Xilinx’s FPGAs and ACAPs, accommodating popular frameworks and the latest deep learning models for a wide array of tasks. It features an extensive collection of pre-optimized models that can be readily deployed on Xilinx devices, allowing users to quickly identify the most suitable model and initiate re-training for specific applications. Additionally, it offers a robust open-source quantizer that facilitates the quantization, calibration, and fine-tuning of both pruned and unpruned models. Users can also take advantage of the AI profiler, which performs a detailed layer-by-layer analysis to identify and resolve performance bottlenecks. Furthermore, the AI library provides open-source APIs in high-level C++ and Python, ensuring maximum portability across various environments, from edge devices to the cloud. Lastly, the efficient and scalable IP cores can be tailored to accommodate a diverse range of application requirements, making this platform a versatile solution for developers.

Ai-rgus employs advanced Artificial Intelligence alongside specially designed software to swiftly identify issues related to camera views, including misconfigurations or failures of cameras, NVRs, and DVRs, incorrect timestamps, and insufficient or missing recording days. By utilizing Ai-rgus, users can significantly reduce the time spent on manual checks while ensuring their surveillance systems capture critical footage before incidents occur. This automation not only enhances efficiency by minimizing the need for manual camera reviews but also supports seamless expansion of camera systems. The AI-driven verification process is dependable and uniform, offering proactive assurance that essential images are available, particularly for incidents like slip and fall cases and theft prevention. With Ai-rgus, users can rest assured that camera verification tasks are completed to a high standard, accompanied by automatic email alerts for any discrepancies that arise. This level of oversight fosters a safer environment by allowing for quick responses to potential security issues.