Best AWS Marketplace Software - Page 89

How Many AWS Marketplace Software Products Does G2 Track?

Total Products under this Category: 2,450

Category Stats (Nov 2026)

  • Average Rating: 4.39/5 The average rating of products in this category, based on all submitted ratings
  • Top Trending Product: GPT-2 XL - Text generation (+3.21%) - Among all products in this category, GPT-2 XL - Text generation recorded the largest rating increase compared to last month

Last updated: November 01, 2026

How Does G2 Rank AWS Marketplace Software Products?

Why You Can Trust G2's Software Rankings:

  • 30 Analysts and Data Experts
  • 30,300+ Authentic Reviews
  • 2,450+ Products
  • Unbiased Rankings

G2's software rankings are built on verified user reviews, rigorous moderation, and a consistent research methodology maintained by a team of analysts and data experts. Each product is measured using the same transparent criteria, with no paid placement or vendor influence. While reviews reflect real user experiences, which can be subjective, they offer valuable insight into how software performs in the hands of professionals. Together, these inputs power the G2 Score, a standardized way to compare tools within every category.

InfraGraf Network Traffic Forecasting

InfraGraf Network Traffic Forecasting helps businesses get a future forecast of the network traffic based on historic data. Benefits offered by this solution includes accurate forecast of network traffic which enables better planning for network infrastructure, application scalability and auto scaling. It uses ensemble ML algorithms with automatic model selection algorithms. This solution provides consistent and better results due to its ensemble learning approach. This solution performs automated model selection to apply the right model based on the input data.

Who Is the Company Behind InfraGraf Network Traffic Forecasting?

  • Seller: Mphasis
  • Year Founded: 2007
  • HQ Location: Reston, VA
  • LinkedIn® Page: www.linkedin.com
    13 employees on LinkedIn®

Infrastructure Ticket Classification

Infrastructure Ticket Classification is a solution designed to automate the categorization and routing of IT service requests using machine learning. By leveraging natural language processing (NLP, it analyzes the content of support tickets to accurately assign them to the appropriate categories and teams, thereby streamlining the resolution process. Key Features and Functionality: - Automated Ticket Categorization: Utilizes NLP to interpret ticket content and assign accurate categories. - Intelligent Routing: Ensures tickets are directed to the appropriate support teams based on classification. - Integration with Existing Systems: Seamlessly integrates with current ticketing platforms to enhance functionality. - Data-Driven Insights: Collects and analyzes classification data to identify trends and opportunities for process improvement. Primary Value and Problem Solved: By automating the classification and routing of support tickets, Infrastructure Ticket Classification reduces manual errors and accelerates response times. This leads to increased operational efficiency, cost savings, and improved customer satisfaction by ensuring that issues are promptly addressed by the appropriate teams.

Who Is the Company Behind Infrastructure Ticket Classification?

  • Seller: Mphasis
  • Year Founded: 2007
  • HQ Location: Reston, VA
  • LinkedIn® Page: www.linkedin.com
    13 employees on LinkedIn®

Ingate SIParator for AWS

Ingate's SIParator® for AWS is a software-based Enterprise Session Border Controller tailored for deployment on Amazon Web Services . It enables secure and seamless SIP-based communications, including VoIP, SIP trunking, and Unified Communications , by integrating with existing network infrastructures. This solution is designed to meet the needs of enterprises of all sizes, from small branch offices to large organizations, by offering customizable options for sessions, remote users, and registrar users. Key Features and Functionality: - SIP Proxy and Registrar: Facilitates the management and routing of SIP traffic within the network. - NAT and PAT Support: Ensures proper traversal of SIP communications through network address translation and port address translation. - TLS and SRTP Encryption: Provides secure SIP signaling and media transmission by encrypting communications. - WebRTC Gateway: Enables interoperability between WebRTC applications and SIP-based systems. - Intrusion Detection and Prevention: Offers security measures to detect and prevent unauthorized access and attacks. - REST API Management: Allows for streamlined configuration and management through a RESTful API. Primary Value and User Solutions: The SIParator® for AWS addresses critical challenges in deploying SIP-based communications by ensuring secure and reliable connectivity across various network environments. It simplifies the integration of SIP trunking services with existing PBX and UC systems, facilitating the connection of remote users and branch offices. By encrypting SIP signaling and media, it mitigates common security concerns associated with enterprise VoIP deployments. Additionally, its compatibility with AWS provides scalability and flexibility, allowing businesses to adapt their communication infrastructure to evolving needs without significant hardware investments.

Who Is the Company Behind Ingate SIParator for AWS?

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Initial Line Assignment

Determine the optimal initial credit line to assign customers with the highest potential.

Who Is the Company Behind Initial Line Assignment?

Initial Rate Plan Assignment

Customers are assigned plans that best meet their needs based on usage during the trial period.

Who Is the Company Behind Initial Rate Plan Assignment?

Inpher XOR Secret Computing Engine

Inpher's XOR Secret Computing Engine is a cutting-edge solution designed to enable secure, privacy-preserving computations on sensitive data without exposing it. By leveraging advanced cryptographic techniques, it allows organizations to perform complex data analyses while maintaining data confidentiality. Key Features and Functionality: - Secure Multi-Party Computation (SMPC: Enables multiple parties to jointly compute functions over their inputs while keeping those inputs private. - Data Confidentiality: Ensures that sensitive information remains encrypted and inaccessible during processing. - Scalability: Designed to handle large datasets and complex computations efficiently. - Integration Flexibility: Compatible with various data sources and analytics platforms, facilitating seamless integration into existing workflows. Primary Value and Problem Solved: The XOR Secret Computing Engine addresses the critical challenge of analyzing sensitive data without compromising privacy. Organizations often face regulatory and ethical constraints when handling confidential information. This solution empowers them to extract valuable insights from their data while ensuring compliance with privacy regulations and safeguarding against data breaches. By enabling secure computations, it fosters collaboration between entities that need to share insights without revealing their proprietary data, thus unlocking new opportunities for data-driven decision-making.

Who Is the Company Behind Inpher XOR Secret Computing Engine?

  • Seller: Inpher
  • Year Founded: 2015
  • HQ Location: New York, US
  • LinkedIn® Page: www.linkedin.com
    8 employees on LinkedIn®

InsightLive BYOL

Equipped with real time intelligence on engineering productivity and quality, InsightLive SDLC is aimed at driving accountability and team synergies coupled with seamless SDLC automation to improve speed and agility.

Who Is the Company Behind InsightLive BYOL?

  • Seller: Virtusa
  • Year Founded: 1996
  • HQ Location: Southborough, Massachusetts, United States
  • LinkedIn® Page: www.linkedin.com
    18,250 employees on LinkedIn®
  • Ownership: NASDAQ: VRTU

Instant AI Ready VSCode Server by Optick

Optick's Instant AI Ready VSCode Server is a cloud-based integrated development environment (IDE) designed to enhance developer productivity by integrating advanced AI capabilities directly into the coding workflow. This turnkey solution provides a secure, browser-accessible version of Visual Studio Code, preconfigured with support for multiple large language models (LLMs) such as GPT-4, CodeLlama, and others. By leveraging this environment, developers can generate, refactor, and debug code with contextual intelligence, streamlining the development process and fostering efficient collaboration. Key Features and Functionality: - Multi-Model Flexibility: Easily switch between various LLM providers, including OpenAI, Hugging Face, Ollama, and private endpoints, through a simple dropdown menu, allowing developers to choose the most suitable model for their specific needs. - Pre-Installed AI Extensions: The environment comes equipped with essential AI tools such as OpenAI Chat and GitHub Copilot, enabling seamless integration and immediate utilization of AI-powered coding assistance without additional setup. - Browser-Based VS Code: Access a secure, high-performance version of Visual Studio Code directly from your browser, eliminating the need for local installations and client-side dependencies, thus simplifying the development setup. - Enterprise-Grade Security: Built on a hardened Ubuntu 24.04 LTS platform, the server includes TLS support, SSH key authentication, and straightforward HTTPS enablement, ensuring robust protection for your code and data. - Scalability and Cost Efficiency: Deploy instances rapidly, scale resources as needed, and reduce costs by hosting private models or utilizing your own API keys, thereby avoiding per-token egress fees associated with external AI services. Primary Value and User Solutions: The Instant AI Ready VSCode Server addresses the growing demand for intelligent coding environments by integrating AI directly into the development process. It accelerates project initiation with AI-powered scaffolding and syntax corrections, enhances code quality through real-time suggestions, and facilitates seamless collaboration by allowing teams to share workspaces and AI sessions for real-time peer review and pair programming. By providing a secure, scalable, and cost-effective solution, it empowers development teams to code smarter and more efficiently, ultimately reducing time-to-market for software products.

Who Is the Company Behind Instant AI Ready VSCode Server by Optick?

Insurance Claims Fraud Detection Model

Claims Fraud is a serious problem for Insurance Companies as it brings down their profits considerably. Currently, This problem is handled using either internal scoring based engines or rely on Third party agencies for investigations. These rule based systems are static in nature and involve lot of manual efforts, making the process slow and prone to errors. To tackle this, Virtusa-GCTS has developed a Machine-Learning based solution which will flag suspect claims as ‘fraud’ and those claims can be subjected to more scrutiny. It uses Boosting based AI models and saves considerable effort.

Who Is the Company Behind Insurance Claims Fraud Detection Model?

  • Seller: Virtusa
  • Year Founded: 1996
  • HQ Location: Southborough, Massachusetts, United States
  • LinkedIn® Page: www.linkedin.com
    18,250 employees on LinkedIn®
  • Ownership: NASDAQ: VRTU

Insurance Customer Churn Prediction

Customer churn refers to the loss of existing clients or customers. This solution identifies insurance customers who are more likely to close/not renew their policies with the insurance provider. During the training stage, the solution automatically conducts feature interaction on the training data and selects a subset of features based on feature importance. It then trains multiple models and identifies the best performing model. This model is then selected for prediction on new data.

Who Is the Company Behind Insurance Customer Churn Prediction?

  • Seller: Mphasis
  • Year Founded: 2007
  • HQ Location: Reston, VA
  • LinkedIn® Page: www.linkedin.com
    13 employees on LinkedIn®

Insurance Policy Data Standardizer

This solution generates a standardized output for input files from various sources containing insurance policy related data.

Who Is the Company Behind Insurance Policy Data Standardizer?

  • Seller: Mphasis
  • Year Founded: 2007
  • HQ Location: Reston, VA
  • LinkedIn® Page: www.linkedin.com
    13 employees on LinkedIn®

intdash

Product Description: intdash is a high-performance middleware platform designed to facilitate rapid and advanced digital transformation across various industries. It provides essential functionalities for building robust IoT platforms, including efficient data transmission, management, and visualization. By leveraging intdash, organizations can swiftly implement core IoT features, allowing them to focus on developing specialized applications and services. Key Features and Functionality: - Low-Latency Real-Time Data Transmission: Utilizes a broker-mediated architecture to achieve end-to-end communication delays within 100 milliseconds in Japan, making it ideal for real-time monitoring and remote control systems. - Reliable Data Storage and Retrieval: Ensures all transmitted data is securely stored on the server, accessible via APIs for versatile use. Features data retrieval capabilities to prevent data loss during network disruptions. - Proprietary Communication Protocol: Employs the patented iSCP (intdash Stream Control Protocol to enable stable and efficient real-time data transmission, even over unstable mobile networks. - High Customizability with API/SDK Support: Offers comprehensive APIs and SDKs, allowing developers to create custom services and applications that integrate seamlessly with intdash. - Proven Performance in Automotive R&D: Extensively utilized in automotive research and development, capable of transmitting hundreds to thousands of data points per second, demonstrating its capacity for handling large-scale data transmission. Primary Value and User Solutions: intdash addresses the challenges of managing and transmitting large volumes of high-frequency, time-series data in real-time. It provides a scalable and reliable data pipeline that supports various industrial applications, including remote monitoring, control, and diagnostics. By integrating intdash, organizations can enhance their IoT capabilities, improve operational efficiency, and accelerate innovation in the digital era.

Who Is the Company Behind intdash?

Intel®DAAL DecisionForest Classification

Intel® DAAL DecisionForest Classification is a high-performance machine learning algorithm designed to handle classification tasks by constructing an ensemble of decision trees. This approach enhances predictive accuracy and robustness by aggregating the outputs of multiple trees, effectively mitigating overfitting and improving generalization to unseen data. Integrated within the Intel® oneAPI Data Analytics Library (oneDAL, this algorithm is optimized for Intel architectures, ensuring efficient execution across various hardware platforms. Key Features and Functionality: - Ensemble Learning: Utilizes multiple decision trees to form a robust classifier, enhancing predictive performance. - Gini Impurity Metric: Employs the Gini index to measure the impurity of nodes, aiding in the optimal splitting of data during tree construction. - Out-of-Bag Error Estimation: Provides an unbiased estimate of the model's prediction error by evaluating the performance on out-of-bag samples, which are not used during the training of individual trees. - Variable Importance Measures: Calculates metrics such as Mean Decrease Impurity (MDI to assess the significance of each feature in the classification process, facilitating feature selection and model interpretability. - Weighted and Unweighted Voting Methods: Offers flexibility in combining individual tree predictions through weighted or unweighted voting, allowing customization based on specific application requirements. Primary Value and Problem Solving: Intel® DAAL DecisionForest Classification addresses the need for scalable and efficient classification algorithms capable of handling large datasets with high-dimensional features. By leveraging ensemble learning techniques, it reduces the risk of overfitting and enhances the model's ability to generalize to new data. The algorithm's optimization for Intel hardware ensures that users can achieve high performance without extensive computational resources. Additionally, features like variable importance measures provide valuable insights into the data, aiding in feature selection and improving model interpretability. This makes it particularly suitable for applications requiring reliable and efficient classification, such as fraud detection, medical diagnosis, and customer segmentation.

Who Is the Company Behind Intel®DAAL DecisionForest Classification?

  • Seller: Intel Corporation
  • Year Founded: 1968
  • HQ Location: Santa Clara, CA
  • LinkedIn® Page: www.linkedin.com
    111,509 employees on LinkedIn®
  • Ownership: NASDAQ:INTC
  • Total Revenue (USD mm): $77,867

Who Uses This Product?

  • Company Size: 100% Large

What Are Recent G2 Reviews of Intel®DAAL DecisionForest Classification?

Intelligent Text Extractor

ITE provides high accuracy text extraction capabilities on printed, hand-printed and hand-written texts. It supports multiple languages, auto-classification of unfamiliar document templates and validations for text type & format. ITE addresses the scaling needs of enterprises for data digitalization as volumes increase, making it efficient to store and standardize data.

Who Is the Company Behind Intelligent Text Extractor?

  • Seller: Marlabs
  • Year Founded: 1996
  • HQ Location: New York, US
  • LinkedIn® Page: www.linkedin.com
    2,358 employees on LinkedIn®

Interoperability Land: Extended

Interoperability Land: Extended is a comprehensive, cloud-based platform designed to facilitate the development, testing, and validation of healthcare interoperability solutions. It offers a simulated environment that mirrors real-world healthcare systems, enabling developers and organizations to create and refine applications that seamlessly exchange health information across diverse systems. Key Features and Functionality: - Realistic Simulation Environment: Provides a virtual healthcare ecosystem with simulated electronic health records (EHRs, patient data, and clinical workflows, allowing for thorough testing of interoperability scenarios. - Support for Standards: Compatible with widely adopted healthcare interoperability standards such as HL7 FHIR (Fast Healthcare Interoperability Resources, ensuring that applications developed within the platform can integrate effectively with existing healthcare systems. - Scalable Infrastructure: Built on a robust cloud infrastructure, the platform can scale to accommodate various testing needs, from small-scale applications to enterprise-level solutions. - Comprehensive Testing Tools: Offers a suite of tools for validating data exchange, assessing system performance, and identifying potential issues in interoperability implementations. Primary Value and Problem Solved: Interoperability Land: Extended addresses the critical challenge of achieving seamless data exchange in the healthcare industry. By providing a realistic and controlled environment for testing interoperability solutions, it enables developers to identify and resolve issues before deployment, reducing the risk of errors in live healthcare settings. This leads to improved patient care through more accurate and timely information sharing, enhanced compliance with industry standards, and accelerated innovation in health IT solutions.

Who Is the Company Behind Interoperability Land: Extended?

Neeraja Prakash
NP
Researched and written by Neeraja Prakash
Updated June 16, 2025