Software Cloud Modernization
Turn your legacy system into SaaS
Run® is the best platform to deploy, operate, integrate, and scale systems and cloud operations.
Modern solutions for software with history
Run modernizes your software offering and accelerates the integration of your legacy system with innovative technologies such as Data and AI — all while giving you transparent, autonomous control over environments, users, and licenses.
No plataform
Saas model without rewriting code
Native cibersecurity layer
Fast deployment and automatic updates
Continuous innovation (Data, AI & more)
Cost optimization
Journey overview
Cloud
PaaS e IaaS
Integration
iPass
Data
Pipeline and Business Insights
AI
Applied Artificial Intelligence
ONE-CLICK DEPLOYMENT: reduce environment provisioning time by up to 100%
– Create environments for your system, speed up deployment, and deliver results dynamically
– Manage multiple databases in an efficient, centralized way
– Keep control of add-ons and licenses to increase visibility over your resources
EFFICIENT VERSIONING: eliminate manual rework when replicating machine updates
– Keep your systems running on the latest version, without interruptions or complexity
– Eliminate risks linked to outdated versions, ensuring greater stability
– Automate the update process, reducing operational effort and downtime
TOTAL DATA CONTROL: manage your backups with practicality, continuity, and security
– Manage backup dates, sizes, and exact schedules
– Easily view your full data history
– Access the complete list of backups in one place
ON-DEMAND SCALABILITY: grow according to your needs
– Automatically expand or reduce operational resources, avoiding unnecessary costs
– High performance even during demand spikes, with dynamic, continuous adjustment
– Scale your operation with agility while maintaining full control and cost predictability
200+ AVAILABLE CONNECTORS: offer the integrations your users want and need
– Connect to leading market tools quickly and simply
– Remove compatibility barriers and improve operational performance
– Avoid long, costly processes for developing multiple APIs
WORKFLOW AUTOMATION: build and automate custom flows
– Integrate multiple tools to drive competitiveness
– Create workflows and automate tasks without relying on advanced coding
– Save time and resources by reducing repetitive manual work
“DATA IS THE NEW OIL”: ensure storage and availability of strategic data
– Centralize the storage of structured, semi-structured, and unstructured data
– Keep data from different sources always within reach
– Support Artificial Intelligence and Machine Learning initiatives
DATA ENGINEERING: turn raw information into business opportunities
– Keep data organized and ready to use
– Design scalable systems that support large data volumes without compromising speed or integrity
– Turn data into innovative, competitive strategies
PERFORMANCE MANAGEMENT: intuitive visibility across sources such as ERP systems and databases
– Track virtual machine performance, per-user costs, and environment volume
– Discover patterns and trends to anticipate challenges and opportunities
– Empower decisions with concrete, real-time data
AI VOICE: artificial intelligence that transcribes, summarizes, and generates strategic insights directly in Run
– Make calls directly from Run with just one click
– Get automatic AI-powered call transcription, creating a complete record of interactions with your contacts
– Generate automatic summaries of the most important information discussed in each cal
Security is not just a feature — it is an integrated experience within Run
Our Cyber Security Layer goes beyond infrastructure, combining robust authentication and continuous monitoring to shield your operations from threats.
Security by Design
Security is not an add-on — it is in Run’s DNA. That is why platform protection is built alongside innovation.
Preemptive Multi-Layer Protection
Security is not an add-on — it is in Run’s DNA. That is why platform protection is built alongside innovation.
Applied Artificial Intelligence
Security is not an add-on — it is in Run’s DNA. That is why platform protection is built alongside innovation.
Hassle-Free Protection
Security is not an add-on — it is in Run’s DNA. That is why platform protection is built alongside innovation.
Immutable and Efficient Backup
A segurança não é um complemento – ela está no DNA do Run. Por isso, toda a proteção da plataforma nasce junto com a inovação.
Efficiency, competitiveness, and closeness for your growth
Autonomy
Run puts you in control, giving you autonomy to access strategic information such as system transaction data, IT resource consumption, versions, and more in a simple, efficient way
Consultative Support
Turn system usage information into valuable insights to identify new sales opportunities, maximize customer satisfaction, and implement technology improvements.
SaaS Transformation
Transform your software offering into a modern, scalable SaaS model, ensuring competitiveness and alignment with market demands.
Strategic Support
Count on a team of specialists to support every stage of your journey, making sure you have the backing you need to focus on the best version of your business.
The experience of those who have seen the future change more than once
Wevy is the first Latin American multinational in cloud computing.
Compute
Digital infrastructure that delivers autonomy and predictability
Software Cloud Modernization
Software modernization platform with no refactoring
Managed Services
Monitoring, support, and sustainment for critical infrastructures
Data & AI - AI no-code
Custom dashboards and enterprise apps built from simple prompts
FAQ
Frequently Asked Questions
What is GPU Cloud and what is it used for?
GPU Cloud is a cloud infrastructure model that provides graphics processing units (GPUs) on demand for compute-intensive workloads.
Unlike traditional infrastructures based mainly on CPUs, GPUs can perform thousands of operations in parallel, which speeds up tasks such as training machine learning models, deep learning, and generative artificial intelligence.
With GPU Cloud, companies can access this processing power without having to invest in their own hardware, using cloud GPUs to develop, train, and run artificial intelligence applications.
What is the difference between CPU and GPU for artificial intelligence?
The CPU (Central Processing Unit) is designed to perform general computing tasks, while the GPU (Graphics Processing Unit) was developed to process large volumes of calculations simultaneously. This parallel processing capability makes GPUs ideal for tasks such as:
- machine learning model training
- processing large volumes of data
- artificial intelligence model inference
- rendering and computational simulation
That is why most modern AI and deep learning projects use GPU-based infrastructure.
When does it make sense to use GPU infrastructure for AI?
GPU-based infrastructure is recommended when applications involve intensive data processing or complex artificial intelligence models. It is especially suitable for:
- training machine learning models
- developing generative AI applications
- running LLMs (Large Language Models)
- processing large volumes of data
- data science and scientific computing workloads
In many cases, the use of GPUs drastically reduces the time required to train or run AI models.
GPU Cloud or on-premises infrastructure: which is better?
For many companies, using cloud GPUs is more efficient than investing in their own infrastructure.
GPU data centers require significant investments in hardware, power, cooling, and maintenance. In the cloud, on the other hand, resources can be provisioned quickly and scaled based on demand.
In addition, GPU Cloud platforms allow engineering and data science teams to focus on developing artificial intelligence models and applications, without having to manage the physical infrastructure.
How much does it cost to use GPU in the cloud?
The cost of GPU Cloud depends on several factors, including:
- the type of GPU used
- the number of instances
- usage time
- storage and network capacity
In general, the pricing model follows an on-demand infrastructure approach, in which companies pay only for the compute resources they use.
This makes it possible to scale artificial intelligence projects flexibly, without the need to invest upfront in specialized hardware.
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