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Prospero.Live is a SaaS pair programming platform featuring a code editor, shared cloud filesystem, video calling, screen sharing, whiteboard, and code runners. It is designed for a super quick collaborative inner development loop where you talk through features, work on code, and see it run all with as few keystokes as possible. You can get started in minutes and there's no need to install anything. It is great for every part of writing code, but excels for prototyping, fixing bugs, interviews, and hanging out all day with another developer demoing snippets of code.

Move your data to the cloud destination of choice where you can start running AI and advanced analytics faster with no downtime. Data Migrator is a fully automated solution that moves on-premise HDFS data, Hive metadata, local filesystem, or cloud data sources to any cloud or on-premises environment, even while those datasets are under active change. Data Migrator requires zero changes to applications or business operations. Moving data of any scale can begin immediately and be performed without production system downtime or business disruption, and with zero risk of data loss.

ASL Recovery Center is Windows desktop software for deleted-file recovery, disk preservation imaging, and inspection of local AI-session and Git artifacts. It is available to individuals and repair technicians as a one-time Microsoft Store purchase. Recovery workflows use read-only scans, a separate output destination, and checksum records. Preservation images can be resumed after interruption. Data stays on the user's computer; the app does not require an account or upload files to a recovery cloud. Recovery depends on what remains on the source. Overwritten, securely erased, or SSD-trimmed data may be unrecoverable. The software does not bypass encryption. The official product page documents supported filesystems, recovery modes, pricing, screenshots, and limitations.

Aquin is an innovative platform designed to empower users to create and manage their own large language models (LLMs) with ease, speed, and cost-effectiveness, all while ensuring complete privacy and security. By integrating seamlessly into daily workflows, Aquin enables individuals and businesses to develop top-tier AI models tailored to their specific needs without requiring extensive machine learning expertise. Key Features and Functionality: - Proactive Floating AI Assistant: Aquin offers a movable, translucent AI assistant interface that overlays existing applications, providing unobtrusive support without disrupting the user's workflow. - Automatic Data Collection: The platform captures and structures data from various sources, including conversations, files (PDFs, documents, spreadsheets, code, images, ZIPs), browser tabs, URLs, YouTube links, audio recordings, Gmail conversations, and Google Drive files. This data is automatically formatted into JSON, JSONL, CSV, or TXT, eliminating the need for manual preprocessing. - Flexible Training Methods: Users can choose from multiple training approaches, such as fine-tuning with Hugging Face models, LoRA (Low-Rank Adaptation), QLoRA (Quantized LoRA), and Retrieval-Augmented Generation (RAG) systems. Training can be conducted locally for enhanced privacy or in the cloud for scalability. - Customizable Training Specifications: Aquin allows users to define training parameters, including device selection (e.g., CUDA or CPU), maximum sequence length, optimizer choice, and memory allocation, providing full control over the training process. - Integration with Third-Party Models: The platform supports connections with external models from providers like OpenAI, Anthropic's Claude, and Ollama, enabling users to leverage a wide range of AI capabilities. - Controlled File-System Protocol (MCP): Aquin includes a secure protocol that permits models to interact with specified directories, files, and tools, facilitating agent-like behavior such as file management and workflow automation without compromising security. Primary Value and User Solutions: Aquin addresses the challenges of AI model development by simplifying the process, reducing costs, and ensuring user privacy. By automating data collection and formatting, it eliminates the need for manual data preparation. The platform's flexible training options and customizable specifications cater to both novices and experts, making AI development accessible to a broader audience. Additionally, Aquin's focus on local processing and controlled integrations ensures that users maintain full ownership and control over their data and models, fostering trust and security in AI applications.

SFTPGo allows to securely share your files over SFTP and optionally FTP/S and WebDAV too.Several storage backends are supported and they are configurable per user, so you can serve a local directory for a user and an S3 bucket (or part of it) for another one.SFTPGo also supports virtual folders, a virtual folder can use any of the supported storage backends. So you can have,for example, an S3 user that exposes a GCS bucket (or part of it) on a specified path and an encrypted local filesystem on another one.Virtual folders can be private or shared among multiple users, for shared virtual folders you can define different quota limits for each user.

Ovrin is a compute cloud platform offering isolated Linux sandboxes for AI coding agents. Each sandbox provides a full Linux environment with a filesystem, network stack, process table, and shell, booting in milliseconds. Using gVisor, it intercepts system calls to contain untrusted code. Sandboxes are provisioned on demand and destroyed after tasks complete. The platform includes pre-configured templates for Claude Code, Codex, Gemini CLI, and DeepSeek Harness, ready to use without Dockerfiles. Chrome and Playwright browsers run within the sandbox, enabling agents to interact with web content, scrape data, and capture screenshots. A persistent memory system stores context across instances. Security features include default-deny egress policies, Kubernetes namespace isolation, and scoped API keys. A unified API with Python and TypeScript SDKs supports compute, memory, browsers, secrets, and payments.

Enter's Litigation product leverages advanced AI agents to enhance the efficiency and success rates of legal teams handling high-volume litigation cases. By conducting exhaustive analyses of defense documents—including contracts, audio, and video files—the platform ensures that all defense arguments are meticulously personalized and clearly presented to the judiciary.

Exabase is the data layer for AI agents. It gives your agents persistent memory, cloud storage, and semantic search so they can remember users, store files, and retrieve context across sessions. The Memory API is a self-organizing memory system that stores facts, preferences, and events, then builds a living knowledge graph that tracks relationships, resolves contradictions, and evolves with every interaction. It's not a vector database. It's real, self-improving memory. The Resources API provides a cloud-native filesystem for agents and users. Store files, notes, bookmarks, and documents with full CRUD, folders, tags, and semantic search built in. The Bases API lets you create isolated cloud workspace instances on demand. Each one comes with its own memory, files, and search, fully controlled by your app and auditable through the API or web console. Stop building memory infrastructure from scratch. Give your agents a place to work.

NudgeHost is a file-hosting service for people and AI agents. Upload any file and get a link in seconds, with no account needed to start. Drop in a PDF, an image, a spreadsheet, a ZIP, or a folder of HTML, and the link is live straight away. Paste HTML directly and it renders as a real page, which makes it a fast way to publish output from Claude, Lovable, Bolt, or v0 without a build step or a deploy pipeline. Free accounts get 10 active links at 25MB a file, QR codes, link expiry, and no branding banner. Paid plans add password protection, larger files, custom domains, and API keys. Files can be replaced in place, so the URL you shared yesterday can point at today's version. Agents get first-class access through a REST API and a Model Context Protocol server, so a tool can create a link and hand it back without a human touching a dashboard.

cigati eml converter for mac allows the user to convert the multiple eml files into multiple file formats like emlx,mbox, HTML, docs, msg, pst and mht. The software also helps us to export the email from eml files to yahoo, Gmail, IMAP, thunderbird, and IMAP. It also gives us the facility to convert the multiple eml files of unlimited size at one go with an extraordinary feature to export the particular eml files by providing the start and end date which can help save time and energy. If you want to spot a file in the system so you can easily find the clues related to your files by the special feature provided by this tool called "easily navigation eml files".This tool also provides you the pause and resume feature with the help of which you can easily pause the backup process if it gets interrupted while uploading and resume it whenever you want.so if you want to use this tool your system needs to fulfill the following basic requirements for easy working of this tool i.e. Pentium class processor, 512 MB of Ram, 50 MB of free space, and enough disk space to store the recovered data. Now, if you are a user from the non-technical background and want to use this product but worried about how to handle it.so, no need to worry as this tool comes with the best GUI based interface which make it easy for the person from non-technical background to easily handle it and one of the best thing about this tool is that it gives you money-back-guarantee i.e. if you are not satisfied with the product so you can ask for the refund of the money. This tool also provides you the various user modes such as single-user mode, administrator mode, technician mode. single-user mode is used when this tool is used by the single user whereas administrator mode is used for the business purpose and technician mode is used for by the technician.

The Nemu Hardened Computing RHEL7 STIG is a pre-configured Amazon Machine Image (AMI) designed to provide a Security Technical Implementation Guide (STIG-hardened Red Hat Enterprise Linux 7 environment. This AMI is tailored for organizations requiring compliance with federal security standards, offering a robust and secure foundation for deploying applications on AWS. Key Features and Functionality: - STIG Compliance: The AMI is fully compliant with STIG guidelines, ensuring that the system adheres to stringent security configurations mandated for federal systems. - Quarterly Updates: The image is updated quarterly to incorporate the latest security patches and compliance measures, maintaining a secure and up-to-date environment. - Enhanced Security Configurations: The AMI includes separate log and home filesystems, providing enhanced security by isolating critical system components. Primary Value and User Benefits: The Nemu Hardened Computing RHEL7 STIG AMI addresses the critical need for secure and compliant computing environments in federal and other high-security sectors. By offering a pre-hardened, STIG-compliant RHEL7 image, it simplifies the deployment process, reduces the time and effort required for manual hardening, and ensures that systems meet necessary security standards from the outset. This solution is particularly valuable for organizations aiming to achieve and maintain compliance with federal security mandates while leveraging the scalability and flexibility of AWS.

Grid.ai, now known as Lightning AI, is a platform designed to streamline the development and scaling of machine learning models by eliminating the complexities associated with infrastructure management. Founded in 2019 by the creators of PyTorch Lightning, the platform enables data scientists and researchers to focus on model development without the need to modify their code for scalability. Key Features and Functionality: - Runs: Scale machine learning code to hundreds of GPUs and model configurations without altering a single line of code. Supports all major ML frameworks and offers features like hyperparameter sweeps, multi-node scaling, native logging, asset management, and cost-effective interruptible pricing. - Datastores: Access vast volumes of data from the cloud as if it were on a local filesystem. Optimized for machine learning operations, allowing training at peak speed without the complexities of cloud storage optimization. - Sessions: Preloaded with JupyterHub and integrated with GitHub, Sessions provide a preconfigured environment for remote development, prototyping, and debugging on the same hardware used for scaling models. Primary Value and User Solutions: Lightning AI addresses the challenges of scaling AI workloads by providing an interface for training models on GPUs and processors without requiring advanced machine learning engineering skills. By handling infrastructure complexities, it allows users to focus on developing and deploying AI models efficiently, reducing the time and cost associated with scaling AI operations.

STON Edge Server Enterprise Edition is a high-performance caching server designed to enhance content delivery and scalability within Amazon Web Services (AWS) environments. Built on a 64-bit asynchronous architecture, it efficiently manages static, dynamic, and media content, ensuring rapid and reliable access for end-users. With capabilities exceeding 10Gbps throughput and handling over 100,000 requests per second, STON Edge Server effectively reduces server load and improves site responsiveness. Key Features and Functionality: - High-Performance Reverse Proxy: Delivers over 10Gbps throughput, processes 100,000 requests per second, and supports 80,000 concurrent sessions with live monitoring capabilities. - Comprehensive Content Caching: Offers robust caching for static and dynamic content, utilizing a POSIX filesystem call for efficient cache management. - Advanced Media Handling: Provides on-the-fly image conversion, video stitching, and seamless ad insertion, optimizing media delivery across diverse devices. Primary Value and User Solutions: STON Edge Server Enterprise Edition addresses the challenges of scaling content delivery by offloading demand from origin servers, thereby reducing latency and enhancing user experience. Its efficient caching mechanisms and high throughput capabilities ensure that websites and applications remain responsive under heavy traffic, leading to improved performance and cost savings. By integrating STON Edge Server into their AWS infrastructure, organizations can achieve scalable, reliable, and efficient content delivery solutions.

WeProof is an online proofing and review platform built for creative agencies, marketing teams, and production companies. Upload images, videos, PDFs, and audio files, organize them in projects, and collect structured client feedback with visual annotations, frame-accurate video comments, and approval workflows. Key features: unlimited reviewers and review rounds on every plan, two-phase review workflow (internal team review → client review), version comparison, visual pin annotations on images and video, one-click approvals, PDF export of review reports, and custom branding. WeProof offers transparent, seat-based pricing starting with a free plan. Designed as a modern, affordable alternative to tools like Filestage, ReviewStudio, and Ziflow — purpose-built for creative agencies with 3–20 team members. EU-hosted infrastructure, GDPR-ready. Visit weproof.studio to start a free trial.

WelsonJS is a Windows-centric JavaScript runtime and automation framework designed for industrial, security-sensitive, and constrained environments where modern runtimes or build tools cannot be assumed. Built on top of native Windows scripting technologies and extended with carefully designed polyfills and native bridges, WelsonJS enables developers to write reliable, auditable, and portable JavaScript automation logic that runs consistently across a wide range of Windows versions—from legacy systems such as Windows 2000/XP to modern Windows 10/11. WelsonJS focuses on deterministic execution, minimal dependencies, and operational transparency, making it suitable for environments such as: * Industrial control systems (ICS/SCADA) * Security testing and cyber-range simulations * Government or enterprise networks with strict software installation policies * Air-gapped or offline systems * Legacy Windows infrastructures that must remain operational The framework provides: * A lightweight JavaScript execution environment without Node.js or modern browsers * Native access to Windows system components (filesystem, networking, processes, COM objects) * Script-based extensibility without build pipelines or package managers * Structured logging, tracing, and error handling for auditability * Optional integration points for cryptography, compression, networking, and automation workflows WelsonJS is developed as an open-source project under the Catswords OSS ecosystem and is intended for research, education, security validation, and industrial automation use cases, rather than consumer-oriented application development. By prioritizing compatibility, control, and survivability under constraints, WelsonJS enables developers to accomplish critical automation and analysis tasks even in adverse or highly restricted environments.

SandboxAQ's Security Suite is a comprehensive, end-to-end solution designed to help organizations identify, manage, and remediate cryptographic vulnerabilities across their entire IT infrastructure. By providing 360-degree visibility into cryptographic assets, the suite enables enterprises to safeguard sensitive data, communications, and transactions against both current and emerging cyber threats, including those posed by quantum computing. Key Features and Functionality: - Comprehensive Cryptographic Inventory: The suite's Discover module offers a thorough inventory of cryptographic assets, including keys, certificates, algorithms, and libraries, across networks, applications, and filesystems. - Vulnerability Detection and Analysis: Utilizing advanced AI-driven analytics, the suite identifies vulnerabilities and policy violations, providing actionable insights for remediation. - Automated Remediation and Enforcement: The Protect module orchestrates automated remediation workflows and enforces protection policies, such as credential rotation and certificate renewal, to maintain compliance and security. - Control Center Dashboard: A centralized dashboard offers real-time monitoring and management of the organization's cryptographic environment, facilitating informed decision-making and policy enforcement. Primary Value and Problem Solved: The Security Suite addresses the critical need for organizations to achieve cryptographic agility in the face of evolving cyber threats and the advent of quantum computing. By providing a unified platform for cryptographic management, it enables enterprises to: - Enhance Security Posture: Gain comprehensive visibility into cryptographic assets, allowing for the identification and remediation of vulnerabilities before they can be exploited. - Ensure Compliance: Maintain adherence to regulatory standards and policies by continuously monitoring and enforcing cryptographic protocols. - Future-Proof Encryption: Prepare for the transition to quantum-resistant cryptography by understanding current cryptographic deployments and planning for necessary upgrades. By integrating advanced AI and quantum technologies, SandboxAQ's Security Suite empowers organizations to proactively manage their cryptographic infrastructure, ensuring robust protection against both present and future cyber threats.

Radar is an open-source Kubernetes visibility tool that runs as a single binary on your laptop or in your cluster - no agents, no CRDs, and no account required. It connects to the Kubernetes API directly and opens a fast web UI in about 30 seconds, working against any conformant cluster (GKE, EKS, AKS, minikube, kind, k3s) and staying airgapped-ready with no external calls. Radar gives you real-time cluster topology and live service-traffic graphs, a resource browser with full CRD auto-discovery, log streaming and pod exec, container image filesystem inspection, a unified event-and-change timeline, and Helm release management (inspect, diff, upgrade, rollback). It includes first-class GitOps support for FluxCD and ArgoCD, OpenCost-powered cost insights, TLS certificate expiry monitoring, and a 31-check cluster audit across security, reliability, and efficiency with NSA/CISA and CIS framework labels and remediation guidance. A built-in MCP server lets AI assistants like Claude, Cursor, and Copilot query your cluster through Radar using token-efficient, read-only-by-default tools. Radar Cloud is the hosted tier for teams. It runs the same open-source engine as an agent in your clusters and adds a multi-tenant control plane: all clusters behind one URL, fleet-wide views (audit failures, package/version drift, expiring certs, cross-cluster resource search), centralized SSO via WorkOS (Google, passkey, Okta, SAML), organizations and roles, invitations, an audit log with CSV export, and Slack/webhook notifications. Because the engine is identical and Kubernetes stays the source of truth, there's no proprietary data format and no lock-in. Radar OSS is free forever under Apache 2.0; Radar Cloud offers a free tier up to 3 clusters plus Team and Enterprise plans.

Denvr AI Cloud is a high-performance, scalable platform designed to accelerate artificial intelligence (AI) development and deployment. It offers a comprehensive suite of services, including AI training, inference, and data science, all integrated within a vertically aligned infrastructure of software, hardware, and data centers located in Canada and the USA. This platform caters to innovators, creators, entrepreneurs, and business leaders seeking efficient and cost-effective AI solutions. Key Features and Functionality: - AI Compute: Provides on-demand or reserved AI compute resources across virtualized and bare metal environments, featuring NVIDIA H100, A100, and Intel Gaudi HPUs. - AI Inference: Offers high-speed, low-cost inference capabilities with fully managed API endpoints for seamless deployment of foundation or custom models. - AI Platform: Enables rapid deployment of private AI factories with pre-integrated compute, networking, and storage solutions. - Developer Platform: Includes Jupyter Notebooks for data exploration, pre-configured machine learning images with current GPU drivers, Docker, and container toolkits, along with APIs and CLI tools for automation. - Infrastructure Highlights: Features high-performance GPU clusters, ultra-fast networking, and scalable filesystems engineered to accelerate training, inference, and production workloads at any scale. Primary Value and Solutions Provided: Denvr AI Cloud addresses the challenges of AI development by offering a robust and flexible infrastructure that simplifies the deployment and scaling of AI workloads. By providing access to cutting-edge hardware and software tools, it reduces setup time, cost, and technical complexity for AI developers. The platform's security-first architecture ensures data privacy and compliance, while its integrated MLOps tools support continuous integration and deployment pipelines. Additionally, Denvr AI Cloud's flexible pricing models, including on-demand and reserved options, allow organizations to optimize costs based on their specific needs. This comprehensive approach empowers users to focus on innovation and accelerate their AI initiatives effectively.

Streambased is a unified event streaming data platform designed to seamlessly integrate real-time and historical data for applications, data lakes, and AI systems. By providing logical views over data in Apache Kafka and Apache Iceberg without the need for data movement or duplication, Streambased enables teams to access and analyze streaming data with confidence and speed. Key Features and Functionality: - Iceberg Service for Kafka (I.S.K.): Projects Kafka topics directly as Apache Iceberg tables, allowing immediate querying of real-time data without duplication. - Analytics Service for Kafka (A.S.K.): Offers a fully distributed SQL engine that integrates with analytics applications supporting JDBC, ODBC, or SQLAlchemy, enabling direct SQL queries on Kafka data. - Storage Service for Kafka (S.S.K.): Provides an Amazon S3-compatible proxy, allowing users to access real-time Kafka data as if it were a filesystem. - Streambased MCP Server: Implements Anthropic's Model Context Protocol standard, enabling AI agents to access real-time data. Primary Value and Solutions Provided: Streambased addresses several challenges faced by organizations dealing with streaming data: - Elimination of ETL Pipelines: By providing logical views over data, Streambased removes the need for complex ETL processes, reducing latency and operational overhead. - Real-Time Data Access: Enables immediate querying of data as it arrives in Kafka, ensuring that dashboards, reports, and AI models are always up-to-date. - Unified Governance: Applies consistent governance policies, including permissions, lineage, and schema evolution, across both operational and analytical applications, ensuring data integrity and compliance. - Performance Optimization: Utilizes indexing techniques to accelerate query performance, delivering up to 100x speed improvements over traditional SQL-on-Kafka solutions. By integrating real-time and historical data without the need for data movement, Streambased provides a single source of truth, enhances data accessibility, and simplifies the data architecture for organizations.

Scrapybara is a cloud-based platform that provides virtual desktop instances tailored for AI agents, enabling them to perform complex computing tasks with ease. By offering remote desktops equipped with essential tools like browsers, code execution environments, and filesystem access, Scrapybara empowers developers to deploy and manage computer-use agents efficiently. The platform supports rapid scaling, allowing users to initiate hundreds of instances within milliseconds, ensuring minimal latency and robust performance. With features such as interactive streaming, authenticated access, and session persistence, Scrapybara simplifies the orchestration and scaling of AI agents, allowing developers to focus on building intelligent solutions without the overhead of managing infrastructure. Key Features and Functionality: - Rapid Deployment: Instantly spin up Ubuntu, Windows, or lightweight Chromium browser instances to suit various computing needs. - Scalability: Effortlessly start hundreds of instances in milliseconds, facilitating large-scale deployments with minimal latency. - Interactive Streaming: Monitor and control instances in real-time, providing immediate feedback and interaction capabilities. - Authenticated Access: Save and load authenticated sessions, enabling seamless access to protected resources without repeated logins. - Session Persistence: Pause and resume instances as needed, ensuring continuity and resource optimization. - Comprehensive Toolset: Utilize pre-built tools like `ComputerTool`, `BashTool`, and `EditTool` to interact with instances programmatically. Primary Value and Problem Solved: Scrapybara addresses the challenge of deploying and managing AI agents that require robust computing environments. By providing scalable, ready-to-use virtual desktops, it eliminates the complexities associated with infrastructure setup and maintenance. This allows developers to focus on creating and refining AI models without being hindered by operational concerns. The platform's speed, scalability, and comprehensive feature set make it an invaluable tool for automating and executing free-form computing tasks at scale.