Find and compare the best Artificial Intelligence software for Azure Blob Storage in 2024
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Use the comparison tool below to compare the top Artificial Intelligence software for Azure Blob Storage on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.
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Google Cloud Platform
Google
Free ($300 in free credits) 55,132 RatingsGoogle Cloud is an online service that lets you create everything from simple websites to complex apps for businesses of any size. Customers who are new to the system will receive $300 in credits for testing, deploying, and running workloads. Customers can use up to 25+ products free of charge. Use Google's core data analytics and machine learning. All enterprises can use it. It is secure and fully featured. Use big data to build better products and find answers faster. You can grow from prototypes to production and even to planet-scale without worrying about reliability, capacity or performance. Virtual machines with proven performance/price advantages, to a fully-managed app development platform. High performance, scalable, resilient object storage and databases. Google's private fibre network offers the latest software-defined networking solutions. Fully managed data warehousing and data exploration, Hadoop/Spark and messaging. -
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Datasaur
Datasaur
$349/month One tool can manage your entire data labeling workflow. We invite you to discover the best way to manage your labeling staff, improve data quality, work 70% faster, and get organized! -
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Edge Delta
Edge Delta
$0.20 per GBEdge Delta is a new way to do observability. We are the only provider that processes your data as it's created and gives DevOps, platform engineers and SRE teams the freedom to route it anywhere. As a result, customers can make observability costs predictable, surface the most useful insights, and shape your data however they need. Our primary differentiator is our distributed architecture. We are the only observability provider that pushes data processing upstream to the infrastructure level, enabling users to process their logs and metrics as soon as they’re created at the source. Data processing includes: * Shaping, enriching, and filtering data * Creating log analytics * Distilling metrics libraries into the most useful data * Detecting anomalies and triggering alerts We combine our distributed approach with a column-oriented backend to help users store and analyze massive data volumes without impacting performance or cost. By using Edge Delta, customers can reduce observability costs without sacrificing visibility. Additionally, they can surface insights and trigger alerts before data leaves their environment. -
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Immuta
Immuta
Immuta's Data Access Platform is built to give data teams secure yet streamlined access to data. Every organization is grappling with complex data policies as rules and regulations around that data are ever-changing and increasing in number. Immuta empowers data teams by automating the discovery and classification of new and existing data to speed time to value; orchestrating the enforcement of data policies through Policy-as-code (PaC), data masking, and Privacy Enhancing Technologies (PETs) so that any technical or business owner can manage and keep it secure; and monitoring/auditing user and policy activity/history and how data is accessed through automation to ensure provable compliance. Immuta integrates with all of the leading cloud data platforms, including Snowflake, Databricks, Starburst, Trino, Amazon Redshift, Google BigQuery, and Azure Synapse. Our platform is able to transparently secure data access without impacting performance. With Immuta, data teams are able to speed up data access by 100x, decrease the number of policies required by 75x, and achieve provable compliance goals. -
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V7
V7
$150A class-agnostic, pixel-perfect automated annotation platform. Built for teams that have a lot of data and strict quality requirements but little time. Ground truth creation can be scaled up 10x. Collaborate with unlimited team members, annotators and seamlessly integrate into your deep learning pipeline. Create ground truth 10x faster with pixel-perfect annotations. Use V7's intuitive tools for labeling data and automating your ML pipelines. The ultimate image and Video Annotation Solution -
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Azure Data Science Virtual Machines
Microsoft
$0.005DSVMs are Azure Virtual Machine Images that have been pre-configured, configured, and tested with many popular tools that are used for data analytics and machine learning. A consistent setup across the team promotes collaboration, Azure scale, management, Near-Zero Setup and full cloud-based desktop to support data science. For one to three classroom scenarios or online courses, it is easy and quick to set up. Analytics can be run on all Azure hardware configurations, with both vertical and horizontal scaling. Only pay for what you use and when you use it. Pre-configured Deep Learning tools are readily available in GPU clusters. To make it easy to get started with the various tools and capabilities, such as Neural Networks (PYTorch and Tensorflow), templates and examples are available on the VMs. ), Data Wrangling (R, Python, Julia and SQL Server). -
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CVAT
CVAT
$33 per monthCVAT, the leading data engine for machine-learning, allows you to annotate better. Teams at all scales use and trust CVAT for data of all sizes. CVAT's intuitive, lightning-fast user interface was developed in collaboration with real-world teams that are solving real-world issues. CVAT is used by the most ambitious AI teams in the world every day, from medical to retail to autonomous cars. CVAT can handle any input data and expected results. It works well with images, videos and even 3D. Bounding boxes and polygons. Points, skeletons. Cuboids. Trajectories. Automated interactive algorithms such as intelligent scissors, histogram equality, and others will help you annotate more efficiently. Get actionable insights from metrics such as the annotator's working hours, the number of objects per hour and more. -
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Quickwork
Quickwork
$20 per monthQuickwork is used by enterprises to create simple and complex workflows. It also allows them to create and publish APIs that are secure, and to manage conversational interactions between employees, customers, and partners. This helps to provide an excellent user experience. Quickwork is an all-in one platform that provides the tools and services needed to build powerful and scalable integrations. It also offers serverless APIs and conversational experiences. Drag and drop applications to create powerful integrations. No need to write a line of code. You can choose from 1000s of apps for business, consumer, analytics, messaging and IoT. Quickwork's API Management allows you to convert any workflow into an REST API in a single click. Our serverless infrastructure allows you to scale your APIs elastically and securely. Create and manage real-time messaging and conversational workflows across multiple channels with human agents, IoT devices, and chatbots. -
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Codebuddy
Codebuddy AI
$10/month Chat about your codebase, and let the AI code assistant update multiple files in your favorite IDE. Include all files you have open in the editor in your next prompt. AI context memory can store up to 128,000 tokens. Let the AI code. You can approve the multi-file fix, a portion of it, or ask for any necessary changes. Codebuddy will scan your repository and create a vector database. Codebuddy can select files or answer questions if you are unfamiliar with your codebase. This is an AI assistant that understands your repository. Create new files or modify multiple files with just one prompt. Codebuddy will automatically insert code for you, in the familiar form of a unified patch (diff). Multi-file support is the industry's leading solution for AI coding. -
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Guild AI
Guild AI
FreeGuild AI is a free, open-source toolkit for experiment tracking. It allows users to build faster and better models by bringing systematic control to machine-learning workflows. It captures all details of training runs and treats them as unique experiments. This allows for comprehensive tracking and analysis. Users can compare and analyse runs to improve their understanding and incrementally enhance models. Guild AI simplifies hyperparameter optimization by applying state-of the-art algorithms via simple commands, eliminating complex trial setups. It also supports pipeline automation, accelerating model creation, reducing errors and providing measurable outcomes. The toolkit runs on all major operating system platforms and integrates seamlessly with existing software engineering applications. Guild AI supports a variety of remote storage types including Amazon S3, Google Cloud Storage and Azure Blob Storage. -
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Scale GenAI Platform
Scale AI
Build, test and optimize Generative AI apps that unlock the value in your data. Our industry-leading ML expertise, our state-of-the art test and evaluation platform and advanced retrieval augmented-generation (RAG) pipelines will help you optimize LLM performance to meet your domain-specific needs. We provide an end-toend solution that manages the entire ML Lifecycle. We combine cutting-edge technology with operational excellence to help teams develop high-quality datasets, because better data leads better AI. -
12
TiMi
TIMi
TIMi allows companies to use their corporate data to generate new ideas and make crucial business decisions more quickly and easily than ever before. The heart of TIMi’s Integrated Platform. TIMi's ultimate real time AUTO-ML engine. 3D VR segmentation, visualization. Unlimited self service business Intelligence. TIMi is a faster solution than any other to perform the 2 most critical analytical tasks: data cleaning, feature engineering, creation KPIs, and predictive modeling. TIMi is an ethical solution. There is no lock-in, just excellence. We guarantee you work in complete serenity, without unexpected costs. TIMi's unique software infrastructure allows for maximum flexibility during the exploration phase, and high reliability during the production phase. TIMi allows your analysts to test even the most crazy ideas. -
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cnvrg.io
cnvrg.io
An end-to-end solution gives you all the tools your data science team needs to scale your machine learning development, from research to production. cnvrg.io, the world's leading data science platform for MLOps (model management) is a leader in creating cutting-edge machine-learning development solutions that allow you to build high-impact models in half the time. In a collaborative and clear machine learning management environment, bridge science and engineering teams. Use interactive workspaces, dashboards and model repositories to communicate and reproduce results. You should be less concerned about technical complexity and more focused on creating high-impact ML models. The Cnvrg.io container based infrastructure simplifies engineering heavy tasks such as tracking, monitoring and configuration, compute resource management, server infrastructure, feature extraction, model deployment, and serving infrastructure. -
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Aporia
Aporia
Our easy-to-use monitor builder allows you to create customized monitors for your machinelearning models. Get alerts for issues such as concept drift, model performance degradation and bias. Aporia can seamlessly integrate with any ML infrastructure. It doesn't matter if it's a FastAPI server built on top of Kubernetes or an open-source deployment tool such as MLFlow, or a machine-learning platform like AWS Sagemaker. Zoom in on specific data segments to track the model's behavior. Unexpected biases, underperformance, drifting characteristics, and data integrity issues can be identified. You need the right tools to quickly identify the root cause of problems in your ML models. Our investigation toolbox allows you to go deeper than model monitoring and take a deep look at model performance, data segments or distribution. -
15
Label Studio
Label Studio
The most flexible data annotation software. Quickly installable. Create custom UIs, or use pre-built labeling template. Layouts and templates that can be customized to fit your dataset and workflow. Detect objects in images. Supported are boxes, polygons and key points. Partition an image into multiple segments. Use ML models to optimize and pre-label the process. Webhooks, Python SDK and API allow you authenticate, create tasks, import projects, manage model predictions and more. ML backend integration allows you to save time by using predictions as a tool for your labeling process. Connect to cloud object storage directly and label data there with S3 and GCP. Data Manager allows you to manage and prepare your datasets using advanced filters. Support multiple projects, use-cases, and data types on one platform. You can preview the labeling interface as you type in the configuration. You can see live serialization updates at the bottom of the page. -
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Robust Intelligence
Robust Intelligence
Robust Intelligence Platform seamlessly integrates into your ML lifecycle to eliminate any model failures. The platform detects weaknesses in your model, detects statistical data issues such as drift, and prevents data from being inserted into your AI system. A single test is the heart of our test-based approach. Each test measures the model's resistance to a particular type of production model failure. Stress Testing runs hundreds upon hundreds of these tests in order to assess model production readiness. These tests are used to automatically configure an AI Firewall to protect the model from the specific types of failures to which it is most vulnerable. Continuous Testing also runs these tests during production. Continuous Testing provides an automated root cause analysis that identifies the root cause of any test failure. ML Integrity can be ensured by using all three elements of Robust Intelligence. -
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Qualytics
Qualytics
Enterprises can manage their data quality lifecycle proactively through contextual data checks, anomaly detection, and remediation. Expose anomalies, metadata and help teams take corrective action. Automate remediation workflows for quick and efficient error resolution. Maintain high data-quality and prevent errors from impacting business decisions. The SLA chart gives an overview of SLA. It includes the total number SLA monitoring performed and any violations. This chart will help you identify data areas that require further investigation or improvements. -
18
Neum AI
Neum AI
No one wants to have their AI respond to a client with outdated information. Neum AI provides accurate and current context for AI applications. Set up your data pipelines quickly by using built-in connectors. These include data sources such as Amazon S3 and Azure Blob Storage and vector stores such as Pinecone and Weaviate. Transform and embed your data using built-in connectors to embed models like OpenAI, Replicate and serverless functions such as Azure Functions and AWS Lambda. Use role-based controls to ensure that only the right people have access to specific vectors. Bring your own embedding model, vector stores, and sources. Ask us how you can run Neum AI on your own cloud. -
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Ikigai
Ikigai
Simulations based on historical data can be used to improve models and update them incrementally. Data governance, access control, and versioning allow for easy collaboration. Ikigai has a wide range of integrations that make it easy to integrate with tools already in your workflow. Ikigai has 200+ connectors that allow you to connect to almost any data source. Want to push your ML to a dashboard or website? Integrate directly using Ikigai’s web integrations. Triggers can be used to run data synchronizations, and retrieve updates every time you run an automation flow. You can integrate Ikigai seamlessly by using your own APIs or creating APIs for your data stack. -
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ModelOp
ModelOp
ModelOp is a leading AI governance tool that helps enterprises safeguard AI initiatives including generative AI and Large Language Models. It also protects in-house vendors, third-party vendors and embedded systems without stifling the innovation. Corporate boards and C suites demand the rapid adoption of generative AI, but face financial risks, regulatory, privacy, security, and ethical issues. Governments at all levels, including federal, state and local, are implementing AI regulations and overseeing the industry quickly. This forces enterprises to prepare and comply with rules that prevent AI from going awry. Connect with AI Governance specialists to stay informed on market trends, regulations and news. You can also get insights and opinions from experts. ModelOp Center helps organizations stay safe and provides peace of mind for all stakeholders. Streamline reporting and compliance across the enterprise. -
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Azure AI Agent Service
Microsoft
Azure AI Agent Service provides a rich set of managed capabilities with a wide range of features. It brings together models, data, services, tools and other resources that enterprises require to automate any business process. Azure AI Agents Service combines the latest models, tools, and technology from Microsoft, OpenAI, and industry-leading companies such as Meta Mistral, Cohere, and Mistral. It also extends your agents' knowledge with Bing, SharePoint and Fabric, Azure AI Search and Azure Blob, and enables taking actions across Microsoft applications and Third-Party apps with Azure Functions, OpenAPI 3.1 specified tools, and Code Interpreter. It also offers an intuitive agent-building experience through Azure AI Foundry, as well
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