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LM-Kit.NETLM-Kit.NET serves as a comprehensive toolkit tailored for the seamless incorporation of generative AI into .NET applications, fully compatible with Windows, Linux, and macOS systems. This versatile platform empowers your C# and VB.NET projects, facilitating the development and management of dynamic AI agents with ease. Utilize efficient Small Language Models for on-device inference, which effectively lowers computational demands, minimizes latency, and enhances security by processing information locally. Discover the advantages of Retrieval-Augmented Generation (RAG) that improve both accuracy and relevance, while sophisticated AI agents streamline complex tasks and expedite the development process. With native SDKs that guarantee smooth integration and optimal performance across various platforms, LM-Kit.NET also offers extensive support for custom AI agent creation and multi-agent orchestration. This toolkit simplifies the stages of prototyping, deployment, and scaling, enabling you to create intelligent, rapid, and secure solutions that are relied upon by industry professionals globally, fostering innovation and efficiency in every project.
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RaimaDBRaimaDB is an embedded time series database designed specifically for Edge and IoT devices, capable of operating entirely in-memory. This powerful and lightweight relational database management system (RDBMS) is not only secure but has also been validated by over 20,000 developers globally, with deployments exceeding 25 million instances. It excels in high-performance environments and is tailored for critical applications across various sectors, particularly in edge computing and IoT. Its efficient architecture makes it particularly suitable for systems with limited resources, offering both in-memory and persistent storage capabilities. RaimaDB supports versatile data modeling, accommodating traditional relational approaches alongside direct relationships via network model sets. The database guarantees data integrity with ACID-compliant transactions and employs a variety of advanced indexing techniques, including B+Tree, Hash Table, R-Tree, and AVL-Tree, to enhance data accessibility and reliability. Furthermore, it is designed to handle real-time processing demands, featuring multi-version concurrency control (MVCC) and snapshot isolation, which collectively position it as a dependable choice for applications where both speed and stability are essential. This combination of features makes RaimaDB an invaluable asset for developers looking to optimize performance in their applications.
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QlooQloo, known as the "Cultural AI," excels in interpreting and predicting global consumer preferences. This privacy-centric API offers insights into worldwide consumer trends, boasting a catalog of hundreds of millions of cultural entities. By leveraging a profound understanding of consumer behavior, our API delivers personalized insights and contextualized recommendations. We tap into a diverse dataset encompassing over 575 million individuals, locations, and objects. Our innovative technology enables users to look beyond mere trends, uncovering the intricate connections that shape individual tastes in their cultural environments. The extensive library includes a wide array of entities, such as brands, music, film, fashion, and notable figures. Results are generated in mere milliseconds and can be adjusted based on factors like regional influences and current popularity. This service is ideal for companies aiming to elevate their customer experience with superior data. Additionally, our premier recommendation API tailors results by analyzing demographics, preferences, cultural entities, geolocation, and relevant metadata to ensure accuracy and relevance.
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Google AI StudioGoogle AI Studio serves as an intuitive, web-based platform that simplifies the process of engaging with advanced AI technologies. It functions as an essential gateway for anyone looking to delve into the forefront of AI advancements, transforming intricate workflows into manageable tasks suitable for developers with varying expertise. The platform grants effortless access to Google's sophisticated Gemini AI models, fostering an environment ripe for collaboration and innovation in the creation of next-generation applications. Equipped with tools that enhance prompt creation and model interaction, developers are empowered to swiftly refine and integrate sophisticated AI features into their work. Its versatility ensures that a broad spectrum of use cases and AI solutions can be explored without being hindered by technical challenges. Additionally, Google AI Studio transcends mere experimentation by promoting a thorough understanding of model dynamics, enabling users to optimize and elevate AI effectiveness. By offering a holistic suite of capabilities, this platform not only unlocks the vast potential of AI but also drives progress and boosts productivity across diverse sectors by simplifying the development process. Ultimately, it allows users to concentrate on crafting meaningful solutions, accelerating their journey from concept to execution.
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SatoriSatori is an innovative Data Security Platform (DSP) designed to facilitate self-service data access and analytics for businesses that rely heavily on data. Users of Satori benefit from a dedicated personal data portal, where they can effortlessly view and access all available datasets, resulting in a significant reduction in the time it takes for data consumers to obtain data from weeks to mere seconds. The platform smartly implements the necessary security and access policies, which helps to minimize the need for manual data engineering tasks. Through a single, centralized console, Satori effectively manages various aspects such as access control, permissions, security measures, and compliance regulations. Additionally, it continuously monitors and classifies sensitive information across all types of data storage—including databases, data lakes, and data warehouses—while dynamically tracking how data is utilized and enforcing applicable security policies. As a result, Satori empowers organizations to scale their data usage throughout the enterprise, all while ensuring adherence to stringent data security and compliance standards, fostering a culture of data-driven decision-making.
What is RapidMiner?
RapidMiner is transforming the landscape of enterprise AI, enabling individuals to influence the future in meaningful ways. The platform equips data enthusiasts across various skill levels to swiftly design and deploy AI solutions that yield immediate benefits for businesses. By integrating data preparation, machine learning, and model operations, it offers a user-friendly experience that caters to both data scientists and non-experts alike. With our Center of Excellence methodology and RapidMiner Academy, we ensure that all customers, regardless of their experience or available resources, can achieve success in their AI endeavors. This commitment to accessibility and effectiveness makes RapidMiner a leader in empowering organizations to harness the power of AI effectively.
What is IBM Watson IoT?
The Internet of Things (IoT) represents a vast network of billions of interconnected physical devices around the world that continuously collect and exchange data. By harnessing IoT data in conjunction with IBM Cloud® technologies, businesses can uncover valuable insights that improve nearly every aspect of their operations and foster the development of cutting-edge business models. Start by connecting your device to an IBM Cloud recipe, using open and lightweight protocols such as MQTT or HTTP for efficient connectivity. Effective management of these connected devices enables applications to access both current and past data seamlessly. Secure APIs play a crucial role in allowing your applications to integrate smoothly with the data produced by these devices, promoting effortless interaction. You have the flexibility to build analytical applications either in the IBM Cloud, on another cloud service, or on your own infrastructure. The IBM Watson IoT® Platform offers a user-friendly approach to quickly connect, collect, and process IoT data. Furthermore, the analytics service can be utilized for powerful visualization and AI-driven analytics in the cloud, resulting in better decision-making and enhanced operational efficiency. This holistic integration not only revolutionizes the way businesses function but also significantly enhances their ability to create value within the digital economy. Ultimately, the transformation brought about by IoT and cloud technologies is reshaping industries and driving innovation at an unprecedented pace.
Integrations Supported
Axon Ivy
Azure Marketplace
Datalytics
IBM Cloud
IBM Cloud Messages for RabbitMQ
IBM Watson IoT Platform
MeaningCloud
RapidProM
TAS Insight Engine
Tableau
Integrations Supported
Axon Ivy
Azure Marketplace
Datalytics
IBM Cloud
IBM Cloud Messages for RabbitMQ
IBM Watson IoT Platform
MeaningCloud
RapidProM
TAS Insight Engine
Tableau
API Availability
Has API
API Availability
Has API
Pricing Information
Free
Free Trial Offered?
Free Version
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
Altair
Date Founded
1985
Company Location
United States
Company Website
rapidminer.com
Company Facts
Organization Name
IBM
Date Founded
1911
Company Location
United States
Company Website
www.ibm.com/cloud/internet-of-things
Categories and Features
Artificial Intelligence
Chatbot
For Healthcare
For Sales
For eCommerce
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)
Big Data
Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates
Business Intelligence
Ad Hoc Reports
Benchmarking
Budgeting & Forecasting
Dashboard
Data Analysis
Key Performance Indicators
Natural Language Generation (NLG)
Performance Metrics
Predictive Analytics
Profitability Analysis
Strategic Planning
Trend / Problem Indicators
Visual Analytics
Data Analysis
Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics
Data Cleansing
Address/ZIP Code Cleaning
Charting
Data Consolidation / ETL
Data Mapping
Multi Data Format Support
Phone/Email Validation
Raw Data Ingestion
Sample Testing
Validation / Matching / Reconciliation
Data Discovery
Contextual Search
Data Classification
Data Matching
False Positives Reduction
Self Service Data Preparation
Sensitive Data Identification
Visual Analytics
Data Extraction
Disparate Data Collection
Document Extraction
Email Address Extraction
IP Address Extraction
Image Extraction
Phone Number Extraction
Pricing Extraction
Web Data Extraction
Data Labeling
Human-in-the-loop
Labeling Automation
Labeling Quality
Performance Tracking
Polygon, Rectangle, Line, Point
SDK
Supports Audio Files
Task Management
Team Collaboration
Training Data Management
Data Mining
Data Extraction
Data Visualization
Fraud Detection
Linked Data Management
Machine Learning
Predictive Modeling
Semantic Search
Statistical Analysis
Text Mining
Data Preparation
Collaboration Tools
Data Access
Data Blending
Data Cleansing
Data Governance
Data Mashup
Data Modeling
Data Transformation
Machine Learning
Visual User Interface
Data Science
Access Control
Advanced Modeling
Audit Logs
Data Discovery
Data Ingestion
Data Preparation
Data Visualization
Model Deployment
Reports
Data Visualization
Analytics
Content Management
Dashboard Creation
Filtered Views
OLAP
Relational Display
Simulation Models
Visual Discovery
Deep Learning
Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization
IoT
Application Development
Big Data Analytics
Configuration Management
Connectivity Management
Data Collection
Data Management
Device Management
Performance Management
Prototyping
Visualization
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization
Natural Language Processing
Co-Reference Resolution
In-Database Text Analytics
Named Entity Recognition
Natural Language Generation (NLG)
Open Source Integrations
Parsing
Part-of-Speech Tagging
Sentence Segmentation
Stemming/Lemmatization
Tokenization
Categories and Features
Data Analysis
Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics
IoT
Application Development
Big Data Analytics
Configuration Management
Connectivity Management
Data Collection
Data Management
Device Management
Performance Management
Prototyping
Visualization