Previsico
Who Is the Company Behind Previsico?
- Seller: Previsico
- Year Founded: 2019
- HQ Location: Loughborough, GB
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LinkedIn® Page: www.linkedin.com
48 employees on LinkedIn®
Total Products under this Category: 474
Last updated: November 01, 2026
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Highlighted products: VMware Cloud Foundation (VCF), Amazon EC2, VMware vSphere, Acronis Cyber Protect Cloud (now Acronis Cyber Platform), Akamai Cloud Computing, DigitalOcean, Google Compute Engine, and Azure Virtual Machines.
Underlying data: [Grid® JSON](https://www.g2.com/categories/infrastructure-as-a-service-iaas/grids.json?focus%5B%5D=vmware-cloud-foundation-vcf&focus%5B%5D=amazon-ec2&focus%5B%5D=vmware-vsphere&focus%5B%5D=acronis-cyber-protect-cloud-now-acronis-cyber-platform&focus%5B%5D=akamai-cloud-computing&focus%5B%5D=digitalocean&focus%5B%5D=google-compute-engine&focus%5B%5D=azure-virtual-machines&segment=all)
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Project Lens is jobsite photo documentation and project coordination software for contractors. It keeps photos, videos, documents, and conversations organized by project and accessible on mobile and web. Teams can capture and annotate jobsite photos, assign tasks, follow checklists, manage schedules, and see who did what and when through project activity history. AI Rundowns turn voice recordings and photos into structured job documentation. The web app includes tools for creating estimates and photo reports. Contractors can share photo galleries and reports with clients to show progress, explain findings, and provide a clear record of completed work, from the first estimate to the final walkthrough.
Property Strength: end-to-end solution for Real Estate Developers. Simplify processes like sales, bookings, real time property inventory, Brokerage, client service, payment milestones, tax, allotment, transfers, invoicing collections and much more.
Proxylity provides fully managed, serverless infrastructure for UDP-based applications. Proxylity UDP Gateway™ gives applications a globally available network endpoint for UDP, DTLS, and WireGuard traffic and delivers that traffic directly to services in the customer's AWS account. Proxylity is delivered as a SaaS offering through the AWS Marketplace. UDP Gateway has AWS Qualified Software status and has completed AWS's Foundational Technical Review (FTR). Proxylity's architecture and engineering practices are aligned with the AWS Well-Architected Framework, including the Serverless Applications and SaaS Lenses. The service is designed to eliminate the need for customers to operate dedicated servers, VM fleets, or container clusters for UDP workloads. Proxylity operates the network infrastructure required to receive, secure, route, and deliver UDP traffic, while application processing and persistent data remain in the customer's AWS environment. Customer traffic can be delivered to AWS Lambda, Step Functions, Kinesis, DynamoDB, S3, CloudWatch, and other AWS services. This separation allows customers to use Proxylity for network connectivity while retaining control of their application logic, data, IAM policies, and AWS environment. Proxylity is designed with security, reliability, and operational simplicity as core architectural requirements. Customer application data is not stored by Proxylity; processing and storage are performed within the customer's AWS account. The service operates across multiple AWS Regions and is designed without single points of failure in its delivery and control planes. Proxylity's goal is straightforward: make developing and operating services that use UDP as simple and low risk as developing and operating services that use HTTP.
PyTorch CPU MKL Production is a pre-configured and fully integrated software stack that combines PyTorch, an open-source machine learning library, with the Python programming language. Designed for high-performance tasks, this stack is optimized for CPU usage, making it suitable for both short and long-running machine learning workloads. It offers a stable and production-ready environment, ensuring long-term support and regular updates. Key Features and Functionality: - High-Performance Execution Environment: Optimized for training and inference tasks on CPU, providing efficient performance for machine learning applications. - Integrated and Tested Software Packages: Includes carefully integrated and tested software components with new features and bug fixes, ensuring reliability and up-to-date functionality. - Stability and Long-Term Support: Offers a stable environment with long-term support and regular updates, making it suitable for production use. Primary Value and User Solutions: PyTorch CPU MKL Production simplifies the deployment of machine learning models by providing a ready-to-use, optimized environment. Users can focus on developing and training models without the overhead of configuring and maintaining the underlying infrastructure. This solution addresses the need for a reliable, high-performance CPU-based platform for machine learning tasks, ensuring stability and efficiency in production settings.
QingCloud's Elastic High-Performance Computing (EHPC service is a cloud-based platform designed to provide scalable, efficient, and secure high-performance computing resources. It caters to a wide range of industries, including scientific research, engineering simulations, life sciences, and artificial intelligence, enabling users to perform complex computations without the need for substantial infrastructure investments. Key Features and Functionality: - High-Performance Computing Resources: EHPC utilizes industry-leading Intel Xeon 6258R CPUs, delivering single-core performance up to 86.4 GFlops, and offers GPU configurations with NVIDIA A100 cards for enhanced computational capabilities. - Flexible Storage Solutions: The platform integrates the Lustre commercial version, a high-performance parallel file system, providing GB-level throughput and millions of IOPS, ensuring efficient data handling. - Dedicated High-Speed Networking: EHPC employs dedicated InfiniBand (IB networks, facilitating high-speed communication between compute nodes and storage, with internal network bandwidth reaching up to 100 Gbps, supporting large-scale parallel processing with low latency. - Elastic Scalability: Users can dynamically adjust computing resources based on workload demands, allowing for on-demand configuration and efficient resource utilization without the need for scheduling, enabling immediate use. - Comprehensive Software Support: EHPC offers over 300 pre-installed applications across various domains, including molecular dynamics, electronic structure calculations, and more, with support for user-defined software installations, ensuring flexibility and adaptability to specific computational needs. - Simplified Operations and Maintenance: The platform handles all aspects of cluster maintenance, network security, and hardware management, allowing users to focus solely on their research and computational tasks without operational concerns. Primary Value and User Solutions: QingCloud EHPC addresses the challenges associated with traditional high-performance computing, such as high costs, complex maintenance, and limited scalability. By offering a cloud-based, elastic, and high-performance computing environment, EHPC enables users to: - Reduce Costs: By eliminating the need for significant hardware investments and offering a pay-as-you-go model, users can access cutting-edge computing resources cost-effectively. - Enhance Efficiency: The platform's high-performance resources and scalable architecture allow for faster computation times, accelerating research and development processes. - Ensure Security and Reliability: With multi-tenant isolation mechanisms and compliance with network security standards, EHPC provides a secure and reliable computing environment, safeguarding user data and operations. Overall, QingCloud EHPC empowers organizations and researchers to perform complex computations efficiently and securely, facilitating innovation and discovery across various fields.
Simply and efficiently host and move workloads between AWS and dedicated colocation in compliant, state-of-the-art QTS data centers.
QuantCAD-Hybrid is an advanced offline-first CAD/CAM estimation and industrial automation software designed for engineering workshops and CNC machining specialists. It features independent 3D STEP feature extraction, precise Material Removal Rate (MRR) calculation, and a local AI-powered copilot running entirely offline to ensure absolute data confidentiality. QuantCAD-Hybrid streamlines order management, automated quote generation, and tool catalog integration without transmitting sensitive CAD data to the cloud.
RackCorp provides dedicated servers and virtual servers hosting services.
Rackdog is a global bare metal server provider specializing in low-latency, high-bandwidth infrastructure solutions for demanding workloads. Across 12+ data center locations, Rackdog helps teams deploy, manage, and scale bare metal without friction.
RackWorks VPS is virtual private server hosting software that offers KVM virtualization, LXC containers, and Windows RDP environments. The platform operates from a Detroit data center connected to Detroit-IX with BGP peers, establishing [redacted] relies on NVMe and SSD technology without spinning disks, while network ports deliver consistent bandwidth. Servers include dedicated IPv4 addresses, IPv6 subnets, and reverse DNS support. Provisioning completes within minutes of setup. Hardware consists of Dell enterprise-grade equipment with Dual Intel Xeon Gold processors. KVM supports Linux, FreeBSD, and OpenBSD operating systems, while LXC optimizes Linux workloads. Windows RDP provides desktop environments with Windows Server editions. A one-click marketplace deploys applications such as WordPress and Docker. Backups protect data, and support staff offer direct assistance. The platform includes flexible scaling options and uptime guarantees.
An infrastructure-as-a-service platform providing AI inference and training systems built on SGLang and Miles frameworks for faster model serving and reinforcement learning.
redu.cloud is a cloud built for AI agents to operate, at agent speed, not human speed. Give an agent one cloud operation: deploy an app, integrate two apps, fix an incident. Every operation is agent and cloud time combined. We cut agent thinking to almost zero, and the waiting for the cloud to a minimum, so machines run at agent speed.