Alternatives to Qualcomm AI
Compare Qualcomm AI alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Qualcomm AI in 2024. Compare features, ratings, user reviews, pricing, and more from Qualcomm AI competitors and alternatives in order to make an informed decision for your business.
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Dialogflow
Google
Dialogflow from Google Cloud is a natural language understanding platform that makes it easy to design and integrate a conversational user interface into your mobile app, web application, device, bot, interactive voice response system, and so on. Using Dialogflow, you can provide new and engaging ways for users to interact with your product. Dialogflow can analyze multiple types of input from your customers, including text or audio inputs (like from a phone or voice recording). It can also respond to your customers in a couple of ways, either through text or with synthetic speech. Dialogflow CX and ES provide virtual agent services for chatbots and contact centers. If you have a contact center that employs human agents, you can use Agent Assist to help your human agents. Agent Assist provides real-time suggestions for human agents while they are in conversations with end-user customers. -
2
Qloo
Qloo
Qloo is the “Cultural AI”, decoding and predicting consumer taste across the globe. A privacy-first API that predicts global consumer preferences and catalogs hundreds of millions of cultural entities. Through our API, we provide contextualized personalization and insights based on a deep understanding of consumer behavior and more than 575 million people, places, and things. Our technology empowers you to look beyond trends and uncover the connections behind people’s tastes in the world around them. Look up entities in our vast library spanning categories like brands, music, film, fashion, travel destinations, and notable people. Results are delivered within milliseconds and can be weighted by factors such as regionalization and real-time popularity. Used by companies who want to incorporate best-in-class data in their consumer experiences. Our flagship recommendation API delivers results based on demographics, preferences, cultural entities, metadata, and geolocational factors. -
3
Google Cloud Speech-to-Text
Google
Google Cloud’s Speech API processes more than 1 billion voice minutes per month with close to human levels of understanding for many commonly spoken languages. Powered by the best of Google's AI research and technology, Google Cloud's Speech-to-Text API helps you accurately transcribe speech into text in 73 languages and 137 different local variants. Leverage Google’s most advanced deep learning neural network algorithms for automatic speech recognition (ASR) and deploy ASR wherever you need it, whether in the cloud with the API, on-premises with Speech-to-Text On-Prem, or locally on any device with Speech On-Device. -
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Fraud.net
Fraud.net
Fraud.net delivers the world’s most advanced infrastructure for fraud management – powered by a sophisticated collective intelligence network, world-class artificial intelligence, and a modern, cloud-based platform that helps you: * Unify fraud data from any source with a single connection * Detect fraudulent activity for 99.5%+ transactions in real-time * Optimize fraud management by uncovering hidden insights in terabytes of data Recognized in Gartner’s Market Guide for Online Fraud Detection, Fraud.net is a real-time, enterprise-strength fraud prevention and analytics solution organized around its business customers’ needs. Through a single point of command, it unifies and analyzes data from disparate systems and sources, tracks digital identities and behaviors, and then deploys the latest tools and technologies to stamp out fraudulent activity while allowing good transactions to sail through. Contact us today for a free trial. -
5
Dataloop AI
Dataloop AI
Manage unstructured data and pipelines to develop AI solutions at amazing speed. Enterprise-grade data platform for vision AI. Dataloop is a one-stop shop for building and deploying powerful computer vision pipelines data labeling, automating data ops, customizing production pipelines and weaving the human-in-the-loop for data validation. Our vision is to make machine learning-based systems accessible, affordable and scalable for all. Explore and analyze vast quantities of unstructured data from diverse sources. Rely on automated preprocessing and embeddings to identify similarities and find the data you need. Curate, version, clean, and route your data to wherever it’s needed to create exceptional AI applications. -
6
TensorFlow
TensorFlow
An end-to-end open source machine learning platform. TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications. Build and train ML models easily using intuitive high-level APIs like Keras with eager execution, which makes for immediate model iteration and easy debugging. Easily train and deploy models in the cloud, on-prem, in the browser, or on-device no matter what language you use. A simple and flexible architecture to take new ideas from concept to code, to state-of-the-art models, and to publication faster. Build, deploy, and experiment easily with TensorFlow.Starting Price: Free -
7
DreamQuark Brain
DreamQuark
AI can be slow, confusing, and costly. Brain empowers wealth managers to make hyper-personalized insights simply and quickly. Serve your clients better and grow smarter with Brain. Turn your data into user-friendly insights in a few clicks to guide your next best action. Brain’s explainable AI gives advisors the reasons behind every recommendation. Use Brain’s CX application or integrate it on your own CX platform and cloud provider. Increase your revenues by predicting which clients will respond best to cross-sell and upsell opportunities. Improve the performance of your campaigns by identifying which clients are likely to take an interest in a product and why. Retain your clients before it’s too late by quickly discovering who is most likely to leave and why. Brain’s explainable AI makes hyper-personalized insights understandable and easier for advisors to act on. Brain simplifies and automates the creation and maintenance of insights, saving you time and money. -
8
Alfi
Alfi
Alfi, Inc. engages in creating interactive digital out-of-home advertising experiences. Alfi utilizes artificial intelligence and computer vision to better serve ads to people. Alfi’s proprietary Ai algorithm understands small facial cues and perceptual details that make potential customers a good candidate for a particular product. The automation works in a way that respects user privacy; without tracking, storing cookies, or using identifiable personal information. Ad agencies are empowered to examine real-time analytics data including interactive experiences, engagement, sentiment, and click-through rate that are otherwise unavailable to out-of-home advertisers. Alfi, powered by AI and machine learning, collects data to understand human behavior for improved analytics with relevant content for a better consumer experience. -
9
OpenVINO
Intel
The Intel Distribution of OpenVINO toolkit makes it simple to adopt and maintain your code. Open Model Zoo provides optimized, pretrained models and Model Optimizer API parameters make it easier to convert your model and prepare it for inferencing. The runtime (inference engine) allows you to tune for performance by compiling the optimized network and managing inference operations on specific devices. It also auto-optimizes through device discovery, load balancing, and inferencing parallelism across CPU, GPU, and more. Deploy your same application across combinations of host processors and accelerators (CPUs, GPUs, VPUs) and environments (on-premise, on-device, in the browser, or in the cloud). -
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Valohai
Valohai
Models are temporary, pipelines are forever. Train, Evaluate, Deploy, Repeat. Valohai is the only MLOps platform that automates everything from data extraction to model deployment. Automate everything from data extraction to model deployment. Store every single model, experiment and artifact automatically. Deploy and monitor models in a managed Kubernetes cluster. Point to your code & data and hit run. Valohai launches workers, runs your experiments and shuts down the instances for you. Develop through notebooks, scripts or shared git projects in any language or framework. Expand endlessly through our open API. Automatically track each experiment and trace back from inference to the original training data. Everything fully auditable and shareable. Automatically track each experiment and trace back from inference to the original training data. Everything fully auditable and shareable.Starting Price: $560 per month -
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Clarifai
Clarifai
Clarifai is a leading AI platform for modeling image, video, text and audio data at scale. Our platform combines computer vision, natural language processing and audio recognition as building blocks for developing better, faster and stronger AI. We help our customers create innovative solutions for visual search, content moderation, aerial surveillance, visual inspection, intelligent document analysis, and more. The platform comes with the broadest repository of pre-trained, out-of-the-box AI models built with millions of inputs and context. Our models give you a head start; extending your own custom AI models. Clarifai Community builds upon this and offers 1000s of pre-trained models and workflows from Clarifai and other leading AI builders. Users can build and share models with other community members. Founded in 2013 by Matt Zeiler, Ph.D., Clarifai has been recognized by leading analysts, IDC, Forrester and Gartner, as a leading computer vision AI platform. Visit clarifai.comStarting Price: $0 -
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Mobius Labs
Mobius Labs
We make it easy to add superhuman computer vision to your applications, devices and processes to give you unassailable competitive advantage. No code, customizable & on-premise AI solutions. -
13
AWS Neuron
Amazon Web Services
It supports high-performance training on AWS Trainium-based Amazon Elastic Compute Cloud (Amazon EC2) Trn1 instances. For model deployment, it supports high-performance and low-latency inference on AWS Inferentia-based Amazon EC2 Inf1 instances and AWS Inferentia2-based Amazon EC2 Inf2 instances. With Neuron, you can use popular frameworks, such as TensorFlow and PyTorch, and optimally train and deploy machine learning (ML) models on Amazon EC2 Trn1, Inf1, and Inf2 instances with minimal code changes and without tie-in to vendor-specific solutions. AWS Neuron SDK, which supports Inferentia and Trainium accelerators, is natively integrated with PyTorch and TensorFlow. This integration ensures that you can continue using your existing workflows in these popular frameworks and get started with only a few lines of code changes. For distributed model training, the Neuron SDK supports libraries, such as Megatron-LM and PyTorch Fully Sharded Data Parallel (FSDP). -
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NaturalText
NaturalText
NaturalText A.I. helps you get more out of your data. Discover relationships, create collections, and unveil hidden insights in documents and other text-based data. NaturalText A.I. uses novel artificial intelligence technology to uncover hidden relationships in data. The software uses various state-of-the-art methods to understand context, analyze patterns, and reveal insights—all in a human-readable way. Reveal insights hidden in your data. Finding everything hidden in your text data is a difficult, if not impossible, task. With traditional search, you can only locate information related to a document. NaturalText A.I., on the other hand, uncovers new information within millions of documents, including scientific papers and patents. Use NaturalText A.I. to reveal insights in the data you are currently missing.Starting Price: $5000.00 -
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Build your deep learning project quickly on Google Cloud: Quickly prototype with a portable and consistent environment for developing, testing, and deploying your AI applications with Deep Learning Containers. These Docker images use popular frameworks and are performance optimized, compatibility tested, and ready to deploy. Deep Learning Containers provide a consistent environment across Google Cloud services, making it easy to scale in the cloud or shift from on-premises. You have the flexibility to deploy on Google Kubernetes Engine (GKE), AI Platform, Cloud Run, Compute Engine, Kubernetes, and Docker Swarm.
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FARO Sphere XG
FARO Technologies, Inc.
FARO Sphere XG is a cloud-based digital reality platform that provides its users a centralized, collaborative experience across the company’s reality capture and 3D modeling applications. When paired with the Stream mobile app, Sphere XG enables faster 3D data capture, processing and project management from anywhere in the world. Sphere XG systematizes every activity while remaining intuitive to navigate, allowing users the ability to better organize their 3D scans and 360° photos alongside 3D models and manage that data across diverse teams around the world. With Sphere XG, 3D point clouds and 360° photo documentation can be viewed and shared all in one place, aligned to a floorplan and viewable over time. Ideal for 4D construction progress management where the ability to compare elements over time is critical, project managers and VDC managers can better democratize data and eliminate the need to use two platforms for their reality capture needs. -
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Strong Analytics
Strong Analytics
Our platforms provide a trusted foundation upon which to design, build, and deploy custom machine learning and artificial intelligence solutions. Build next-best-action applications that learn, adapt, and optimize using reinforcement-learning based algorithms. Custom, continuously-improving deep learning vision models to solve your unique challenges. Predict the future using state-of-the-art forecasts. Enable smarter decisions throughout your organization with cloud based tools to monitor and analyze. The process of taking a modern machine learning application from research and ad-hoc code to a robust, scalable platform remains a key challenge for experienced data science and engineering teams. Strong ML simplifies this process with a complete suite of tools to manage, deploy, and monitor your machine learning applications. -
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DeepCube
DeepCube
DeepCube focuses on the research and development of deep learning technologies that result in improved real-world deployment of AI systems. The company’s numerous patented innovations include methods for faster and more accurate training of deep learning models and drastically improved inference performance. DeepCube’s proprietary framework can be deployed on top of any existing hardware in both datacenters and edge devices, resulting in over 10x speed improvement and memory reduction. DeepCube provides the only technology that allows efficient deployment of deep learning models on intelligent edge devices. After the deep learning training phase, the resulting model typically requires huge amounts of processing and consumes lots of memory. Due to the significant amount of memory and processing requirements, today’s deep learning deployments are limited mostly to the cloud. -
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Accelerate your deep learning workload. Speed your time to value with AI model training and inference. With advancements in compute, algorithm and data access, enterprises are adopting deep learning more widely to extract and scale insight through speech recognition, natural language processing and image classification. Deep learning can interpret text, images, audio and video at scale, generating patterns for recommendation engines, sentiment analysis, financial risk modeling and anomaly detection. High computational power has been required to process neural networks due to the number of layers and the volumes of data to train the networks. Furthermore, businesses are struggling to show results from deep learning experiments implemented in silos.
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Neural Magic
Neural Magic
GPUs bring data in and out quickly, but have little locality of reference because of their small caches. They are geared towards applying a lot of compute to little data, not little compute to a lot of data. The networks designed to run on them therefore execute full layer after full layer in order to saturate their computational pipeline (see Figure 1 below). In order to deal with large models, given their small memory size (tens of gigabytes), GPUs are grouped together and models are distributed across them, creating a complex and painful software stack, complicated by the need to deal with many levels of communication and synchronization among separate machines. CPUs, on the other hand, have large, much faster caches than GPUs, and have an abundance of memory (terabytes). A typical CPU server can have memory equivalent to tens or even hundreds of GPUs. CPUs are perfect for a brain-like ML world in which parts of an extremely large network are executed piecemeal, as needed. -
21
Analance
Ducen
Combining Data Science, Business Intelligence, and Data Management Capabilities in One Integrated, Self-Serve Platform. Analance is a robust, salable end-to-end platform that combines Data Science, Advanced Analytics, Business Intelligence, and Data Management into one integrated self-serve platform. It is built to deliver core analytical processing power to ensure data insights are accessible to everyone, performance remains consistent as the system grows, and business objectives are continuously met within a single platform. Analance is focused on turning quality data into accurate predictions allowing both data scientists and citizen data scientists with point and click pre-built algorithms and an environment for custom coding. Company – Overview Ducen IT helps Business and IT users of Fortune 1000 companies with advanced analytics, business intelligence and data management through its unique end-to-end data science platform called Analance. -
22
FortressIQ
Automation Anywhere
FortressIQ enables enterprises to decode work, transform experiences, and enhance workflows with the industry’s most advanced process intelligence platform. Using innovative computer vision and artificial intelligence, FortressIQ delivers unprecedented process insights, extremely fast, and with detail and accuracy unattainable with traditional methods. The platform autonomously acquires process data at scale even as processes extend across systems, empowering enterprises to understand, monitor, and improve operations, employee and customer experiences, and every business process. FortressIQ was founded in 2017, and is backed by Lightspeed Venture Partners, Boldstart Ventures, Comcast Ventures, Eniac Ventures, M12 and Tiger Global. Pinpoint inefficiencies and process variations continuously and automatically to reveal optimal process paths and reduce time to automation. -
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Cauliflower
Cauliflower
Whether for a service or a product, whether a snapshot or monitoring over time - Cauliflower processes feedback and comments from various application areas. Using Artificial Intelligence (AI), Cauliflower identifies the most important topics, their relevance, evaluation and relationships. In-house developed machine learning models for the extraction of content and evaluation of sentiment. Intuitive dashboards with filter options and drill-downs. Use included variables for language, weight, ID, time or location. Define your own filter variables in the dropdown. Cauliflower translates the results into a uniform language if required. Define a company-wide language about customer feedback instead of reading it sporadically and quoting individual opinions. -
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RazorThink
RazorThink
RZT aiOS offers all of the benefits of a unified artificial intelligence platform and more, because it's not just a platform — it's a comprehensive Operating System that fully connects, manages and unifies all of your AI initiatives. And, AI developers now can do in days what used to take them months, because aiOS process management dramatically increases the productivity of AI teams. This Operating System offers an intuitive environment for AI development, letting you visually build models, explore data, create processing pipelines, run experiments, and view analytics. What's more is that you can do it all even without advanced software engineering skills. -
25
Mintrics
Mintrics
Mintrics is the ultimate social video analytics dashboard, with market and competitor intelligence. It lets brands, agencies, and content creators understand exactly which videos are performing well, which aren't, and why. With Mintrics, all of your videos across Facebook and YouTube are analyzed in one place. It connects to the various APIs using the users' tokens to gather data that is not available publicly, runs all sorts of calculations and displays unique metrics with historical data. But since metrics are useless on their own, Mintrics offers benchmarks, monthly reports, and personalized recommendations. First, on a page/channel level to clearly indicate how a given video's performing against the rest, and then industry benchmarks that show performance against the competition at large. You also get to track & group your competitors in lists and view the market insights in whole using Mintrics live leaderboard!Starting Price: $79 -
26
Lambda GPU Cloud
Lambda
Train the most demanding AI, ML, and Deep Learning models. Scale from a single machine to an entire fleet of VMs with a few clicks. Start or scale up your Deep Learning project with Lambda Cloud. Get started quickly, save on compute costs, and easily scale to hundreds of GPUs. Every VM comes preinstalled with the latest version of Lambda Stack, which includes major deep learning frameworks and CUDA® drivers. In seconds, access a dedicated Jupyter Notebook development environment for each machine directly from the cloud dashboard. For direct access, connect via the Web Terminal in the dashboard or use SSH directly with one of your provided SSH keys. By building compute infrastructure at scale for the unique requirements of deep learning researchers, Lambda can pass on significant savings. Benefit from the flexibility of using cloud computing without paying a fortune in on-demand pricing when workloads rapidly increase.Starting Price: $1.25 per hour -
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Produvia
Produvia
Produvia is a serverless machine-learning development service. Partner with Produvia to develop and deploy machine models using serverless cloud infrastructure. Fortune 500 companies and Global 500 enterprises partner with Produvia to develop and deploy machine learning models using modern cloud infrastructure. At Produvia, we use state-of-the-art methods in machine learning and deep learning technologies to solve business problems. Organizations overspend on infrastructure costs. Modern organizations use serverless architectures to reduce server costs. Organizations are held back by complex servers and legacy code. Modern organizations use machine learning technologies to rewrite technology stacks. Companies hire software developers to write code. Modern companies use machine learning to develop software that writes code.Starting Price: $1,000 per month -
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Metacoder
Wazoo Mobile Technologies LLC
Metacoder makes processing data faster and easier. Metacoder gives analysts needed flexibility and tools to facilitate data analysis. Data preparation steps such as cleaning are managed reducing the manual inspection time required before you are up and running. Compared to alternatives, is in good company. Metacoder beats similar companies on price and our management is proactively developing based on our customers' valuable feedback. Metacoder is used primarily to assist predictive analytics professionals in their job. We offer interfaces for database integrations, data cleaning, preprocessing, modeling, and display/interpretation of results. We help organizations distribute their work transparently by enabling model sharing, and we make management of the machine learning pipeline easy to make tweaks. Soon we will be including code free solutions for image, audio, video, and biomedical data.Starting Price: $89 per user/month -
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Segmind
Segmind
Segmind provides simplified access to large computing. You can use it to run your high-performance workloads such as Deep learning training or other complex processing jobs. Segmind offers zero-setup environments within minutes and lets your share access with your team members. Segmind's MLOps platform can also be used to manage deep learning projects end-to-end with integrated data storage and experiment tracking. ML engineers are not cloud engineers and cloud infrastructure management is a pain. So, we abstracted away all of it so that your ML team can focus on what they do best, and build models better and faster. Training ML/DL models take time and can get expensive quickly. But with Segmind, you can scale up your compute seamlessly while also reducing your costs by up to 70%, with our managed spot instances. ML managers today don't have a bird's eye view of ML development activities and cost.Starting Price: $5 -
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DataRobot
DataRobot
AI Cloud is a new approach built for the demands, challenges and opportunities of AI today. A single system of record, accelerating the delivery of AI to production for every organization. All users collaborate in a unified environment built for continuous optimization across the entire AI lifecycle. The AI Catalog enables seamlessly finding, sharing, tagging, and reusing data, helping to speed time to production and increase collaboration. The catalog provides easy access to the data needed to answer a business problem while ensuring security, compliance, and consistency. If your database is protected by a network policy that only allows connections from specific IP addresses, contact Support for a list of addresses that an administrator must add to your network policy (whitelist). -
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Comet
Comet
Manage and optimize models across the entire ML lifecycle, from experiment tracking to monitoring models in production. Achieve your goals faster with the platform built to meet the intense demands of enterprise teams deploying ML at scale. Supports your deployment strategy whether it’s private cloud, on-premise servers, or hybrid. Add two lines of code to your notebook or script and start tracking your experiments. Works wherever you run your code, with any machine learning library, and for any machine learning task. Easily compare experiments—code, hyperparameters, metrics, predictions, dependencies, system metrics, and more—to understand differences in model performance. Monitor your models during every step from training to production. Get alerts when something is amiss, and debug your models to address the issue. Increase productivity, collaboration, and visibility across all teams and stakeholders.Starting Price: $179 per user per month -
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Ray
Anyscale
Develop on your laptop and then scale the same Python code elastically across hundreds of nodes or GPUs on any cloud, with no changes. Ray translates existing Python concepts to the distributed setting, allowing any serial application to be easily parallelized with minimal code changes. Easily scale compute-heavy machine learning workloads like deep learning, model serving, and hyperparameter tuning with a strong ecosystem of distributed libraries. Scale existing workloads (for eg. Pytorch) on Ray with minimal effort by tapping into integrations. Native Ray libraries, such as Ray Tune and Ray Serve, lower the effort to scale the most compute-intensive machine learning workloads, such as hyperparameter tuning, training deep learning models, and reinforcement learning. For example, get started with distributed hyperparameter tuning in just 10 lines of code. Creating distributed apps is hard. Ray handles all aspects of distributed execution.Starting Price: Free -
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Neural Designer
Artelnics
Neural Designer is a powerful software tool for developing and deploying machine learning models. It provides a user-friendly interface that allows users to build, train, and evaluate neural networks without requiring extensive programming knowledge. With a wide range of features and algorithms, Neural Designer simplifies the entire machine learning workflow, from data preprocessing to model optimization. In addition, it supports various data types, including numerical, categorical, and text, making it versatile for domains. Additionally, Neural Designer offers automatic model selection and hyperparameter optimization, enabling users to find the best model for their data with minimal effort. Finally, its intuitive visualizations and comprehensive reports facilitate interpreting and understanding the model's performance.Starting Price: $2495/year (per user) -
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Domino Enterprise MLOps Platform
Domino Data Lab
The Domino platform helps data science teams improve the speed, quality, and impact of data science at scale. Domino is open and flexible, empowering professional data scientists to use their preferred tools and infrastructure. Data science models get into production fast and are kept operating at peak performance with integrated workflows. Domino also delivers the security, governance and compliance that enterprises expect. The Self-Service Infrastructure Portal makes data science teams become more productive with easy access to their preferred tools, scalable compute, and diverse data sets. The Integrated Model Factory includes a workbench, model and app deployment, and integrated monitoring to rapidly experiment, deploy the best models in production, ensure optimal performance, and collaborate across the end-to-end data science lifecycle. The System of Record allows teams to easily find, reuse, reproduce, and build on any data science work to amplify innovation. -
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CloudMinds
CloudMinds
To operate smart robots for people, currently we build and operate an open end-to-end cloud robot system, and offer it as a service to the world. Our pioneering world-class architecture connects robots and smart devices over a secure Virtual Backbone Networks (VBNs) to Cloud AI. Our Human Augmented Robotics Intelligence with Extreme Reality (HARIX) platform is an ever evolving “cloud brain” capable of operating millions of cloud AI robots performing different tasks simultaneously. Complemented by our smart joint technology (SCA), our cloud AI capabilities include Natural Language Processing (NLP), Computer Vision (CV), navigation, and vision-controlled manipulation that’s bringing a vibrant cloud ecosystem of next generation robotics and smart devices to many industry value chains. -
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Deci
Deci AI
Easily build, optimize, and deploy fast & accurate models with Deci’s deep learning development platform powered by Neural Architecture Search. Instantly achieve accuracy & runtime performance that outperform SoTA models for any use case and inference hardware. Reach production faster with automated tools. No more endless iterations and dozens of different libraries. Enable new use cases on resource-constrained devices or cut up to 80% of your cloud compute costs. Automatically find accurate & fast architectures tailored for your application, hardware and performance targets with Deci’s NAS based AutoNAC engine. Automatically compile and quantize your models using best-of-breed compilers and quickly evaluate different production settings. Automatically compile and quantize your models using best-of-breed compilers and quickly evaluate different production settings. -
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Keras
Keras
Keras is an API designed for human beings, not machines. Keras follows best practices for reducing cognitive load: it offers consistent & simple APIs, it minimizes the number of user actions required for common use cases, and it provides clear & actionable error messages. It also has extensive documentation and developer guides. Keras is the most used deep learning framework among top-5 winning teams on Kaggle. Because Keras makes it easier to run new experiments, it empowers you to try more ideas than your competition, faster. And this is how you win. Built on top of TensorFlow 2.0, Keras is an industry-strength framework that can scale to large clusters of GPUs or an entire TPU pod. It's not only possible; it's easy. Take advantage of the full deployment capabilities of the TensorFlow platform. You can export Keras models to JavaScript to run directly in the browser, to TF Lite to run on iOS, Android, and embedded devices. It's also easy to serve Keras models as via a web API. -
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Automation Hero
Automation Hero
Automation Hero's end-to-end platform takes a democratized, bottom-up approach to intelligent automation. With a no-code GUI, users can easily build automations ranging from mundane and manual works tasks and complex business processes, adding in AI at any point without relying on data scientists or IT. The platform includes Hero_Sonar for process mining, Hero_Go for screen scraping, AI Studio to upload or build/train AI models and Flow Studio to build automation flows (with optional AI models) and Robin, Automation Hero’s personal automation assistant, for human-in-the-loop integration. Robin also serves as a feedback loop to improve AI models. Automation Hero is available on-premise or in the cloud. Pricing is consumption-based and includes built-in orchestration.Starting Price: $6 per node -
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Caffe
BAIR
Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research (BAIR) and by community contributors. Yangqing Jia created the project during his PhD at UC Berkeley. Caffe is released under the BSD 2-Clause license. Check out our web image classification demo! Expressive architecture encourages application and innovation. Models and optimization are defined by configuration without hard-coding. Switch between CPU and GPU by setting a single flag to train on a GPU machine then deploy to commodity clusters or mobile devices. Extensible code fosters active development. In Caffe’s first year, it has been forked by over 1,000 developers and had many significant changes contributed back. Thanks to these contributors the framework tracks the state-of-the-art in both code and models. Speed makes Caffe perfect for research experiments and industry deployment. Caffe can process over 60M images per day with a single NVIDIA K40 GPU. -
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ML Kit
Google
ML Kit brings Google’s machine learning expertise to mobile developers in a powerful and easy-to-use package. Make your iOS and Android apps more engaging, personalized, and helpful with solutions that are optimized to run on device. ML Kit’s processing happens on-device. This makes it fast and unlocks real-time use cases like processing of camera input. It also works while offline and can be used for processing images and text that need to remain on the device. Take advantage of the machine learning technologies that power Google's own experiences on mobile. We combine best-in-class machine learning models with advanced processing pipelines and offer these through easy-to-use APIs to enable powerful use cases in your apps. Recognizes handwritten text and handdrawn shapes on a digital surface, such as a touch screen. Recognizes 300+ languages, emojis and basic shapes. -
41
AWS Inferentia
Amazon
AWS Inferentia accelerators are designed by AWS to deliver high performance at the lowest cost for your deep learning (DL) inference applications. The first-generation AWS Inferentia accelerator powers Amazon Elastic Compute Cloud (Amazon EC2) Inf1 instances, which deliver up to 2.3x higher throughput and up to 70% lower cost per inference than comparable GPU-based Amazon EC2 instances. Many customers, including Airbnb, Snap, Sprinklr, Money Forward, and Amazon Alexa, have adopted Inf1 instances and realized its performance and cost benefits. The first-generation Inferentia has 8 GB of DDR4 memory per accelerator and also features a large amount of on-chip memory. Inferentia2 offers 32 GB of HBM2e per accelerator, increasing the total memory by 4x and memory bandwidth by 10x over Inferentia. -
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ONTAP AI
NetApp
D-I-Y has its place, like weed control. Building out your AI infrastructure is another story. ONTAP AI consolidates a data center’s worth of analytics, training, and inference compute into a single, 5-petaflop AI system. Powered by NVIDIA DGX™ systems and NetApp cloud-connected all-flash storage, NetApp ONTAP AI helps you fully realize the promise of AI and deep learning (DL). You can simplify, accelerate, and integrate your data pipeline with the ONTAP AI proven architecture. Streamline the flow of data reliably and speed up analytics, training, and inference with your data fabric that spans from edge to core to cloud. NetApp ONTAP AI is one of the first converged infrastructure stacks to incorporate NVIDIA DGX A100, the world’s first 5-petaflop AI system, and NVIDIA Mellanox® high-performance Ethernet switches. You get unified AI workloads, simplified deployment, and fast return on investment. -
43
Zebra by Mipsology
Mipsology
Zebra by Mipsology is the ideal Deep Learning compute engine for neural network inference. Zebra seamlessly replaces or complements CPUs/GPUs, allowing any neural network to compute faster, with lower power consumption, at a lower cost. Zebra deploys swiftly, seamlessly, and painlessly without knowledge of underlying hardware technology, use of specific compilation tools, or changes to the neural network, the training, the framework, and the application. Zebra computes neural networks at world-class speed, setting a new standard for performance. Zebra runs on highest-throughput boards all the way to the smallest boards. The scaling provides the required throughput, in data centers, at the edge, or in the cloud. Zebra accelerates any neural network, including user-defined neural networks. Zebra processes the same CPU/GPU-based trained neural network with the same accuracy without any change. -
44
IntelliHub
Spotflock
We work closely with businesses to find out what are the common issues preventing companies from realising benefits. We design to open up opportunities that were previously not viable using conventional approaches Corporations -big and small, require an AI platform with complete empowerment and ownership. Tackle data privacy and adopt to AI platforms at a sustainable cost. Enhance the efficiency of businesses and augment the work humans do. We apply AI to gain control over repetitive or dangerous tasks and bypass human intervention, thereby expediting tasks with creativity and empathy. Machine Learning helps to give predictive capabilities to applications with ease. You can build classification and regression models. It can also do clustering and visualize different clusters. It supports multiple ML libraries like Weka, Scikit-Learn, H2O and Tensorflow. It includes around 22 different algorithms for building classification, regression and clustering models. -
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FeedStock Synapse
FeedStock
FeedStock’s state of the art multi-lingual deep learning technology captures, identifies and extracts vital information present in your communication channels and turns it into high-value actionable insights. A typical buying decision jumped from needing 17 contacts in 2019 to 27 in 2021. B2B buying has changed, there are more interactions, less face time and outbound growth is getting harder. We provide fully automated intelligent assistance to drive revenue across your relationship-driven sales teams. By analysing your client interactions straight from your inbox we can deliver untapped growth with hidden insights. We deliver immediate time to value, don’t worry about costly long adoption cycles. When you switch on FeedStock it is ready to go. 10 times more relationships captured and categorised, millions of topics extracted and unrivalled proprietary insights that drive growth for your business. -
46
Wolfram Mathematica
Wolfram
The world's definitive system for modern technical computing. For three decades, Mathematica has defined the state of the art in technical computing—and provided the principal computation environment for millions of innovators, educators, students, and others around the world. Widely admired for both its technical prowess and elegant ease of use, Mathematica provides a single integrated, continually expanding system that covers the breadth and depth of technical computing—and is seamlessly available in the cloud through any web browser, as well as natively on all modern desktop systems. With energetic development and consistent vision for three decades, Mathematica stands alone in a huge range of dimensions, unique in its support for today's technical computing environments and workflows.Starting Price: $1,520 per year -
47
Abacus.AI
Abacus.AI
Abacus.AI is the world's first end-to-end autonomous AI platform that enables real-time deep learning at scale for common enterprise use-cases. Apply our innovative neural architecture search techniques to train custom deep learning models and deploy them on our end to end DLOps platform. Our AI engine will increase your user engagement by at least 30% with personalized recommendations. We generate recommendations that are truly personalized to individual preferences which means more user interaction and conversion. Don't waste time in dealing with data hassles. We will automatically create your data pipelines and retrain your models. We use generative modeling to produce recommendations that means even with very little data about a particular user/item you won't have a cold start. -
48
ClearML
ClearML
ClearML is the leading open source MLOps and AI platform that helps data science, ML engineering, and DevOps teams easily develop, orchestrate, and automate ML workflows at scale. Our frictionless, unified, end-to-end MLOps suite enables users and customers to focus on developing their ML code and automation. ClearML is used by more than 1,300 enterprise customers to develop a highly repeatable process for their end-to-end AI model lifecycle, from product feature exploration to model deployment and monitoring in production. Use all of our modules for a complete ecosystem or plug in and play with the tools you have. ClearML is trusted by more than 150,000 forward-thinking Data Scientists, Data Engineers, ML Engineers, DevOps, Product Managers and business unit decision makers at leading Fortune 500 companies, enterprises, academia, and innovative start-ups worldwide within industries such as gaming, biotech , defense, healthcare, CPG, retail, financial services, among others.Starting Price: $15 -
49
Agara
Agara
Agara is the world's leading Real-time Voice AI SaaS platform that processes customer support calls in real-time to eliminate hold time, reduce manual inputs and improve customer experience. Agara significantly improves customer satisfaction (CX) scores while reducing support costs by over 50%. -
50
Automaton AI
Automaton AI
With Automaton AI’s ADVIT, create, manage and develop high-quality training data and DNN models all in one place. Optimize the data automatically and prepare it for each phase of the computer vision pipeline. Automate the data labeling processes and streamline data pipelines in-house. Manage the structured and unstructured video/image/text datasets in runtime and perform automatic functions that refine your data in preparation for each step of the deep learning pipeline. Upon accurate data labeling and QA, you can train your own model. DNN training needs hyperparameter tuning like batch size, learning, rate, etc. Optimize and transfer learning on trained models to increase accuracy. Post-training, take the model to production. ADVIT also does model versioning. Model development and accuracy parameters can be tracked in run-time. Increase the model accuracy with a pre-trained DNN model for auto-labeling.