Best AWS Marketplace Software - Page 149

Tehama

Tehama is the industry’s most advanced enclave hosting platform. Tehama securely connects people to sensitive data and systems without the complexity. Developed in the cloud with a focus on end-users and service providers, Tehama Technologies’ cybersecurity platform offers an innovative and disruptive approach to addressing today's digital security and AI challenges. It delivers standardized, policy-based security across the enterprise, requiring zero infrastructure. This approach not only enhances the user risk profile but also ensures immediate ROI ‘out of the box’ by eliminating the need for complex and endless integration of component technologies. No more layering multiple tools or vendors, just rapid, policy-based control over how, where, and by whom data is accessed. Tehama simplifies compliance with CMMC, SOC 2 Type 2, ISO 27001, PCI and more while enabling AI governance, auditability, and complete data containment. Whether you’re securing third-party vendors, managing distributed teams, or protecting Controlled Unclassified Information (CUI), Tehama delivers the confidence and control you need to operate safely and compliantly in today’s threat environment.

Teleskope

Teleskope is a data security platform (DSPM/DLP) that helps security teams discover, classify, and automatically remediate sensitive data exposure across cloud, SaaS, collaboration, database, and AI environments — without manual triage or external remediation tools or ticketing. Designed primarily for CISOs, security operations, and GRC teams at mid-market and enterprise organizations, Teleskope addresses a gap that exists across the data security category: most platforms identify where sensitive data lives but provide no native mechanism to act on what they find. Teleskope combines deep classification with a built-in remediation engine, allowing organizations to move from finding risk to closing it in the same platform. At the core of the platform is a proprietary Data Reasoning Layer — an intelligence architecture that understands business context rather than matching against predefined patterns. This allows Teleskope to classify sensitive documents based on what they are and what they mean in a given environment, not just what regulated fields they contain. A draft M&A term sheet, a proprietary engineering formula, or a sealed legal record can each be identified as sensitive without a rule that says look for it. Key capabilities include: - Automated native remediation — inform, redact, quarantine, revoke access, relocate, or delete, enforced directly within the platform based on your policies, with no handoff to a ticketing system or external tool - Flexible deployment — air-gapped, single-tenant SaaS, or multi-tenant SaaS, covering regulated government and defense environments through to cloud-first enterprises - Broad connector coverage — cloud infrastructure (AWS, GCP, Azure), SaaS (Salesforce, ServiceNow, Workday), collaboration (Slack, Google Drive, Microsoft 365), databases (Snowflake, BigQuery, PostgreSQL), and AI tools (Microsoft Copilot, OpenAI, Claude) - AI data governance — classifies data before it reaches AI agents and copilots, blocks sensitive transfers to external LLMs, and governs what internal AI systems are trained on - Compliance-ready reporting — automated audit evidence for SOC 2, ISO 27001, HIPAA, PCI-DSS, GDPR, CCPA, and EU AI Act, with a full remediation log for every automated action. Key value propositions include: - Reduced risk exposure — high-confidence data exposure is remediated automatically and continuously, shrinking the attack surface in seconds rather than days. - Lower operational burden — security teams are freed from manual alert triage; customers report approximately one hour per week of active platform management after initial deployment. - Reduced legal and compliance liability — enforced retention policies eliminate data that has outlived its purpose, reducing what is discoverable in litigation, subject to breach. notification requirements, and exposed in regulatory inquiries. - Responsible AI adoption — security teams gain visibility and control over what data AI tools can reach before deployment, enabling organizations to adopt AI without creating ungoverned data exposure. - Faster time to value than legacy platforms — a crawl, walk, run deployment model brings customers from initial data map to governed automation in approximately six months. Teleskope is used by organizations in fintech, professional services, healthcare, hospitality, manufacturing, and the public sector, including Ramp, GoFundMe, The Atlantic, Aprio, Alloy, and Chevron Phillips.

Average Rating: 4.8/5.0

Total Reviews: 12

TensorFlow 1.5 Python 2.7 NVidia GPU CUDA 9.1 Production on Ubuntu

The "TensorFlow 1.5 Python 2.7 NVidia GPU CUDA 9.1 Production on Ubuntu" is an Amazon Machine Image (AMI) designed to provide a ready-to-use environment for deep learning applications. This AMI integrates TensorFlow 1.5 with Python 2.7, optimized for NVIDIA GPUs using CUDA 9.1, all running on the Ubuntu operating system. It offers a streamlined setup for developers and researchers aiming to leverage GPU acceleration for machine learning tasks. Key Features and Functionality: - Pre-configured Environment: The AMI comes with TensorFlow 1.5 and Python 2.7 pre-installed, reducing the time and effort required for setup. - GPU Optimization: Utilizes NVIDIA GPUs with CUDA 9.1 support, enabling efficient execution of computationally intensive deep learning models. - Ubuntu OS: Built on the stable and widely-used Ubuntu operating system, ensuring compatibility and reliability. - Scalability: Easily scalable on AWS EC2 instances, allowing users to adjust resources based on project requirements. Primary Value and Problem Solved: This AMI addresses the challenges associated with setting up a deep learning environment by providing a pre-configured, GPU-optimized platform. Users can focus on developing and training machine learning models without the complexities of manual installation and configuration. By leveraging this AMI, developers and researchers can accelerate their workflows, reduce setup time, and ensure compatibility between TensorFlow, CUDA, and the underlying hardware.

TensorFlow 1.5 Python 3.6 NVidia GPU CUDA 9.1 Production on Ubuntu

The "TensorFlow 1.5 Python 3.6 NVidia GPU CUDA 9.1 Production on Ubuntu" Amazon Machine Image (AMI) is a pre-configured environment designed to streamline the development and deployment of deep learning applications. This AMI integrates TensorFlow 1.5 with Python 3.6, optimized for NVIDIA GPUs using CUDA 9.1, all within an Ubuntu operating system. Key Features and Functionality: - Pre-Configured Environment: Eliminates the need for manual setup by providing a ready-to-use deep learning framework. - TensorFlow 1.5 Integration: Offers compatibility with models and codebases developed for TensorFlow 1.5. - Python 3.6 Support: Ensures compatibility with a wide range of Python libraries and tools. - NVIDIA GPU Optimization: Utilizes CUDA 9.1 to leverage GPU acceleration, enhancing computational performance. - Ubuntu Operating System: Provides a stable and widely-used Linux environment for development. Primary Value and Problem Solved: This AMI addresses the complexities associated with setting up a deep learning environment by offering a pre-configured solution. Users can focus on developing and deploying machine learning models without the overhead of configuring software dependencies and ensuring hardware compatibility. By leveraging GPU acceleration through CUDA 9.1, it significantly reduces training times, making it ideal for production-level deep learning tasks.

TensorFlow 1.5 Python 3.6 NVidia GPU CUDA 9 Production

The TensorFlow 1.5 Python 3.6 NVidia GPU CUDA 9 Production AMI is a pre-configured, fully integrated software stack designed for machine learning and deep learning applications. It combines TensorFlow 1.5, Python 3.6, and CUDA 9, optimized for NVidia GPU acceleration, providing a stable and tested execution environment for training, inference, or running as an API service. This AMI is tailored for both short and long-running high-performance tasks and can be seamlessly integrated into continuous integration and deployment workflows. Key Features and Functionality: - Pre-configured Environment: Includes TensorFlow 1.5, Python 3.6, and CUDA 9, eliminating the need for manual setup and configuration. - GPU Optimization: Leverages NVidia GPU acceleration to enhance computational performance for machine learning tasks. - Stability and Reliability: Provides a tested and stable environment suitable for production workloads. - Integration Capabilities: Designed to fit seamlessly into continuous integration and deployment pipelines, facilitating efficient development workflows. Primary Value and Problem Solved: This AMI addresses the challenges associated with setting up and configuring a machine learning environment by offering a ready-to-use, optimized stack. Users can focus on developing and deploying machine learning models without the overhead of environment setup, ensuring efficient use of resources and time. The integration with NVidia GPUs ensures that computational tasks are performed with high efficiency, making it ideal for both development and production scenarios.

TensorFlow CPU MKL Production

TensorFlow CPU MKL Production is a pre-configured runtime environment designed for machine learning tasks, integrating TensorFlow with Intel's Math Kernel Library (MKL to enhance performance on CPU-based systems. This setup is particularly beneficial for users seeking optimized training and inference capabilities without the need for GPU resources. Key Features and Functionality: - Optimized Performance: Leverages Intel MKL to accelerate deep learning computations on CPUs, providing significant speed improvements over standard CPU configurations. - Pre-Configured Environment: Includes TensorFlow, Keras, Python, and Jupyter Notebook, offering a ready-to-use platform for developing and deploying machine learning models. - Development Tools: Comes equipped with essential development tools such as C compilers and build utilities, facilitating a seamless development experience. Primary Value and User Solutions: This product addresses the need for high-performance machine learning environments on CPU infrastructure, making it ideal for users without access to GPUs or those preferring CPU-based deployments. By integrating Intel MKL, it ensures efficient execution of complex computations, reducing training and inference times. The inclusion of popular libraries and tools in a pre-configured setup simplifies the development process, allowing users to focus on model building and experimentation without the overhead of environment setup.

TeraDact S3 Batch Redact

"What would take me 1 week, took me 30 minutes." That's how one UK police officer described RedactorPlus — and it captures why forces, municipalities and public sector bodies are replacing manual redaction with AI. RedactorPlus by TeraDact is a complete AI-powered redaction platform covering every format your disclosure obligations touch: Documents — PDF, Office, ODF, email and AutoCAD, with configurable rulesets Video — AI facial recognition with real-time tracking, vehicle registration detection, and bulk body-worn video processing Audio — speech detection and selective removal, speaker isolation, and transcription with keyword detection Images — faces, logos, plates and user-defined features, with batch processing The AI does the exhaustive detection work at 95% accuracy; your reviewers validate and approve every redaction, with a full audit trail. The result: an 80% reduction in redaction time. In one policing deployment, 4 out of 5 officers previously tied up in redaction returned to core duties. Your data never leaves your environment. Patented local AI processing means content is never sent to external AI services — the data protection exposure that undermines most cloud AI redaction tools simply doesn't exist. Deploy as SaaS with data residency compliance, on-premises, hybrid, or fully air-gapped. Built for FOI/FOIA requests, subject access requests, body-worn video disclosure, criminal investigation evidence and bulk anonymisation. Trusted by UK police forces and Dutch municipalities, integrated with NICE Investigate, and available on the UK Home Office national AI Redaction Framework. ISO 27001 | SOC 2 | Cyber Essentials Plus | ISO 27017 | ISO 27018

Terracloudx EKS-optimized AMI with GPU Support

Terracloudx offers this software product repackaged where additional charges apply for technical support provided by Terracloudx and includes EKS-optimized AMI with GPU, email

Terracloudx LAMP and PhpMyAdmin Oneclick

LAMP and PhpMyAdmin is the software group of different open source programs that are installed together, with the aim of enabling a server as a provider of dynamic web page services, as well as web applications. With the proportion of a coding framework it allows you to start the creation of your websites and apps much faster

Terracloudx Mautic Pro OneClick

Terracloudx Mautic Pro OneClick is an all-in-one digital tool for marketing automation that from a single platform, allows you to manage and execute inbound marketing campaigns in a comprehensive way.

Terracloudx NGINX Oneclick

NGINX Open Source is a lightweight and high-performance server capable of serving content to a high volume of connections. It is primarily adopted for its reliability, security, stability, and low resource consumption. It is used by high-demanding websites due to its asynchronous architecture and ideal for handling heavy loads. NGINX Open Source is simple to configure, and it can be extended with 3rd party modules. It is an essential component of the LEMP stack.

TerraHub - DevOps Hub for Terraform Automation

TerraHub is a comprehensive DevOps platform designed to streamline and automate Terraform workflows, facilitating efficient provisioning and management of cloud resources across multiple accounts and providers. Its ecosystem comprises three core components: - TerraHub CLI: An open-source command-line tool that automates and orchestrates Terraform executions, enabling the creation and management of Terraform configurations with ease. - TerraHub API: A centralized layer for data and log management, collecting and organizing information from Terraform operations to provide a unified view of infrastructure activities. - TerraHub Console: A user-friendly graphical interface that displays real-time Terraform executions, offering enterprise-grade auditing and reporting capabilities for comprehensive oversight. Key Features and Functionality: - Centralized Real-Time Dashboards: Provides a unified view of cloud resources and Terraform executions across multiple accounts and regions, enhancing visibility and control. - Reliable and Enforceable Automation: Automates the provisioning and management of various cloud resources, including virtual machines, containers, and serverless services, ensuring consistency and reliability. - Data-Driven Decision Making: Utilizes machine learning and artificial intelligence to analyze cloud resource management data, enabling informed and proactive decisions. Primary Value and Problem Solved: TerraHub addresses the complexities associated with managing large-scale cloud infrastructures by automating Terraform workflows and providing centralized management tools. This automation reduces operational overhead, minimizes human error, and accelerates deployment processes. By offering real-time insights and comprehensive reporting, TerraHub empowers organizations to make data-driven decisions, optimize resource utilization, and enhance overall operational efficiency.

Terra Security

Terra Security is a comprehensive cybersecurity solution designed to protect organizations from a wide range of digital threats. By integrating advanced threat detection, real-time monitoring, and proactive defense mechanisms, Terra Security ensures the safety and integrity of sensitive data and systems. Its user-friendly interface and scalable architecture make it suitable for businesses of all sizes, providing robust protection without compromising performance. Key Features and Functionality: - Advanced Threat Detection: Utilizes machine learning algorithms to identify and neutralize emerging threats before they can cause harm. - Real-Time Monitoring: Offers continuous surveillance of network activities, promptly alerting administrators to any suspicious behavior. - Proactive Defense Mechanisms: Implements automated responses to detected threats, minimizing potential damage and reducing response times. - User-Friendly Interface: Provides an intuitive dashboard that simplifies the management and monitoring of security protocols. - Scalable Architecture: Adapts to the needs of various organizations, from small businesses to large enterprises, ensuring optimal performance regardless of scale. Primary Value and Solutions Provided: Terra Security addresses the critical need for robust cybersecurity in an increasingly digital world. By offering advanced threat detection and real-time monitoring, it empowers organizations to proactively defend against cyberattacks, safeguarding sensitive information and maintaining operational continuity. Its scalable design and user-friendly interface ensure that businesses can implement effective security measures without requiring extensive technical expertise, thereby enhancing overall resilience against digital threats.

Tetra R&D Data Cloud

The Tetra R&D Data Cloud provides life sciences companies with the flexibility, scalability, and data-centric capabilities to enable easy access to centralized, standardized, and actionable scientific data and is actively deployed across enterprise pharma and biotech organizations.

Tevico

Tevico is a cloud governance platform for your AWS cloud. With Tevico, you get guidance with respect to Cloud financial management, security management, inventory management and many more things which are crucial for your AWS governance. Additionally, Tevco has automation features which allow you to automate your cloud management workflows.