Products

The AISE PyTorch 0.4 Python 3.6 CPU Notebook is a pre-configured, fully integrated runtime environment designed for machine learning and data science applications. It combines PyTorch 0.4, an open-source machine learning library, with Python 3.6 and Jupyter Notebook, a browser-based interactive platform for programming and data analysis. Optimized for CPU performance, this environment facilitates efficient development and execution of machine learning models without the need for GPU resources.

Selenium Grid on Windows is a preconfigured Amazon Machine Image (AMI) designed to facilitate the deployment of Selenium Grid within a Windows Server environment. This solution enables users to execute automated tests across multiple browsers and platforms, streamlining the testing process for web applications. Key Features and Functionality: - Preinstalled Selenium Grid: The AMI comes with Selenium Grid set up, allowing for immediate deployment and use. - Multi-Browser Support: It includes p

Keiro is a developer-first web search and scraping API designed for AI systems that need high-quality, human-written sources, not SEO spam or AI-generated junk. Unlike traditional search APIs, Keiro automatically detects and filters AI-generated content, SEO spam, and promotional pages, ensuring your LLMs are grounded in reliable, factual sources. Every result includes a 0–100 quality score, giving developers full control over what content enters their retrieval or RAG pipeline. Keiro i

The AISE TensorFlow 1.8 Python 2.7 CUDA 9.1 Production is a pre-configured and fully integrated software stack designed for machine learning and deep learning applications. It combines TensorFlow 1.8, Python 2.7, and CUDA 9.1 to provide a stable and tested execution environment optimized for NVIDIA GPUs. This setup is ideal for training, inference, and running API services, and can be seamlessly integrated into continuous integration and deployment workflows. Key Features and Functionality: -

The AISE PyTorch 0.4 Python 3.6 CUDA 9.1 Notebook is a pre-configured, fully integrated runtime environment designed for machine learning and data science applications. It combines PyTorch 0.4, an open-source machine learning library, with Python 3.6 and Jupyter Notebook, providing a seamless platform for developing and deploying deep learning models. Optimized for NVIDIA GPUs, this environment leverages CUDA 9.1 to accelerate computations, making it ideal for both training and inference tasks.

The AISE TensorFlow 1.10 Python 3.6 CUDA 9.2 Production AMI is a pre-configured Amazon Machine Image designed to streamline the deployment of deep learning applications on AWS. It integrates TensorFlow 1.10 with Python 3.6 and CUDA 9.2, providing a ready-to-use environment that eliminates the complexities of manual setup. This AMI is optimized for high-performance computing, enabling developers and data scientists to efficiently build, train, and deploy machine learning models on Amazon EC2 inst

TensorFlow, an open source software library for machine learning, and Python, a high-level programming language for general-purpose programming

The AISE TensorFlow 1.10 Python 2.7 CUDA 9.2 Notebook is a pre-configured, fully integrated runtime environment designed for deep learning applications. It combines TensorFlow 1.10, Python 2.7, and NVIDIA CUDA 9.2, providing a seamless platform for developing and deploying machine learning models. This environment is optimized for high-performance execution, enabling efficient training and inference processes. Key Features and Functionality: - TensorFlow 1.10 Integration: Leverages the capabil

The AISE TensorFlow 1.10 Python 3.6 CUDA 9.2 Notebook is a pre-configured, fully integrated runtime environment designed for machine learning and deep learning applications. It combines TensorFlow 1.10, Python 3.6, and CUDA 9.2, providing a robust platform for developing and deploying complex models. This environment is optimized for high-performance execution, ensuring efficient training and inference processes. Key Features and Functionality: - TensorFlow 1.10 Integration: Offers the capabil

Python and Django developer marketplace.

Lightweight client library for writing agario bots in Python

Mlxtend (machine learning extensions) is a Python library of useful tools for the day-to-day data science tasks.

ARTIK Cloud is an open data exchange platform for the Internet of Things (IoT).

Playwright on Headless Ubuntu is a preconfigured Amazon Machine Image designed to facilitate seamless browser automation and testing. Hosted on Ubuntu 24.04 LTS, this environment is optimized for executing headless Playwright tests, enabling developers to automate interactions across multiple browser engines, including Chromium , Firefox, and WebKit . The AMI comes equipped with sample code snippets and preinstalled language bindings for Python, Node.js, and Java, providing a convenient starting

EasyEngine (ee) is a python tool to easily manage your WordPress websites with NGINX, supported on Ubuntu and Debian Linux Distributions.

Lapis Data Analytics is a dynamic data engineering company dedicated to transforming raw data into strategic business assets. With extensive experience in web crawling, data extraction, and enrichment, Lapis delivers high-quality, customized data solutions that empower organizations to make informed decisions and drive growth. Their services encompass data cleansing, transformation, and visualization, ensuring that clients receive meaningful insights tailored to their specific needs. Key Featu

Neurolab is a simple and powerful Neural Network Library for Python that contains based neural networks, train algorithms and flexible framework to create and explore other neural network types.

Vulners is curating the largest correlated database of vulnerabilities and exploits and offers the tool for a customised vulnerability management solution, through API, Python SD, plugins and ready to use Linux Scanner.

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

Reproducible Experiment Platform (REP) is a software infrastructure to support collaborative ecosystem for computational science it is a Python based solution for research teams that allows running computational experiments on shared datasets, obtaining repeatable results, and consistent comparisons of the obtained results.