Provectus Managed Services
Reinvent your IT operations, optimize and secure your technology infrastructure, and achieve operational excellence on AWS with 24/7 expert managed services
Drive growth and innovation for your business on AWS
Amid increasing competitive pressures, businesses today cannot waste the resources of their IT departments to handle routine operational tasks and manage AWS, or other cloud, environments.
With Provectus Managed Services, you can rest assured that your cloud environments are safe, secure, and optimized for cost-efficiency and compliance. Get 24/7 engineering support by our AWS-certified team, to stay focused on your core business operations!
Achieve Your Strategic Goals with Provectus Managed Services
Align internal and external resources to eliminate redundancies and minimize risks in day-to-day IT operations
Reduce labor and IT costs by moving away from a capital expense model and freeing up the resources of your engineering teams
Enhance IT security with 24/7 monitoring and protection of your networks, data, infrastructure, and other components of the AWS environment
Stay focused on your core business operations by eliminating the complexities of cloud environments
The adoption of AI in financial services is driven by the need to improve efficiency, reduce costs, enhance customer experience, and stay competitive. By leveraging the power of AI, financial institutions can transform their operations to better serve their customers.
Major AI use cases include: fraud detection and prevention, risk assessment and management, personalized recommendations, customer service, trading, underwriting, financial planning and advice.
Organizations in HCLS are adopting AI to improve patient care and outcomes, reduce costs, improve efficiency, and bring new treatments to market more quickly and efficiently. With AI, healthcare providers and life science companies can better serve their patients and customers.
Major AI use cases include: personalized medicine, medical diagnosis, medical imaging, treatment planning, population health management, drug discovery and development, clinical trial recruitment, automation of redundant tasks (e.g. document processing).
Manufacturers adopt AI to increase efficiency, improve quality, enhance decision-making, and facilitate product customization. AI helps to optimize production processes and reduce waste, leading to significant cost savings.
Major AI use cases include: predictive maintenance and analytics, quality control and assurance, production planning and scheduling, supply chain optimization, product customization, energy optimization.
Retailers and CPG companies adopt AI to gain a competitive edge by moving faster and making better decisions than their competitors. AI drives various efficiencies, from enhanced decision-making and better customer service, to cost reduction.
Major AI use cases include: customer service chatbots and personalized interactions, inventory management, fraud detection, supply chain management and optimization, pricing optimization, product development, marketing and advertising spend management.
AI improves transportation and logistics operations by optimizing vehicle routing and scheduling, predicting vehicle maintenance needs, and analyzing various sensor data. AI can help streamline operations, reduce costs, and improve service levels.
Major AI use cases include: route optimization and management, predictive maintenance for vehicles, warehouse optimization and management, demand forecasting, fraud detection, energy optimization.
AI helps energy and utilities companies to improve efficiency, increase reliability, and reduce costs. These advantages are essential in industries where margins are tight. AI also helps to identify new business opportunities and detect areas with potential for growth.
Major AI use cases include: predictive maintenance of equipment and systems, energy consumption forecasting and optimization, network optimization, fraud detection, personalized customer service.
AI has every tool for the media and entertainment industry to create better, more personalized and engaging experiences for audiences. It can help to increase ad sales by allowing for personalized, real-time ad insertions.
Major AI use cases include: personalized content recommendations, audience analytics, churn prediction, optimization of advertising and marketing campaigns, automatic content optimization for search, content creation.
AI enables genetics and biotech organizations to improve the efficiency and accuracy of research, increase profitability, and enhance the development and delivery of medical treatments. It can also dramatically reduce the risk of errors and oversight.
Major AI use cases include: at-scale analysis of genetic data, drug discovery and development, personalized medicine and personalized treatment recommendations, genetic diagnosis, clinical trial recruitment, disease diagnosis and prediction.
With AI, organizations can develop new products and services much faster and more effectively than their rivals. The adoption of AI in IT & software development can significantly improve processes, increase efficiency, and enhance the quality of products and services offered.
Major AI use cases include: AI-supported development of AI/ML products and services, AI chatbots for customer service, automated code generation and completion, automated testing, CI/CD-related automation, various data analytics use cases.
Managed Services help to automate the training, testing and deployment of ML models. This can include everything from building and testing models using various algorithms and frameworks, to deploying models to production environments.
Managed Services offer robust tools for monitoring and management of deployed models, including model performance monitoring and timely model updates.
Managed Services enable efficient communication, collaboration, and work sharing among Data Scientists and Data and ML Engineers, boosting performance and productivity.
Managed Services provide tools for efficient management and storage of data used to train and evaluate ML models. They also include tools for data wrangling, cleaning, and preprocessing.
Managed Services help ensure that ML projects adhere to compliance and security standards. They come with potent tools for data governance, and data privacy and security.
Managed Services provide tools and services for cost-effective cloud infrastructure management. These include tools for provisioning, configuring, and resource scaling.
Managed Services help optimize cloud costs by providing tools for efficient tracking and forecasting of resource usage. They also help identify opportunities for cost savings.
Managed Services provide useful tools and services for timely implementation of disaster recovery and backup plans, including tools for backup and recovery automation.
Managed Services ensure that cloud infrastructure is designed and built in accordance with best security and compliance standards. They offer tools for efficient monitoring and managing access to cloud resources.
Managed Services make it easier to deploy and manage various applications in the cloud. They come with all necessary tools for continuous integration and delivery (CI/CD).
Managed Services can help to automate and optimize business processes, with various tools for decision-making, process automation, and resource allocation.
Managed Services enable you to simplify the process of integrating data from multiple sources. They offer a variety of tools for extracting, transforming, and loading (ETL) data.
Managed Services help to ensure that data is secure and compliant, with tools for data access management and enforcement of specific data governance policies.
Managed Services provide tools and services for analyzing and visualizing data, including tools for handling reports, dashboards, and other data-driven insights.
Managed data pipelines make it easy to process and analyze data, with tools for data visualization, data mining, and machine learning.
Managed AI can be used to develop applications that recognize and classify images and speech. Such applications cover facial recognition, object recognition, and voice recognition.
Managed AI can help to build predictive models for forecasting future outcomes based on historical data. Such models can be used for financial forecasting, customer churn prediction, and demand prediction.
Managed AI can be applied to building applications that understand and process human language, including applications for language translation, text classification, and sentiment analysis.
Managed AI can help to build systems for detecting and preventing fraudulent activity, including credit card fraud detection, insurance fraud detection, and money laundering.
Managed AI can be used to build applications that personalize content and make recommendations based on user behavior and preferences, including applications for targeted advertising and product recommendation.
Managed AI can be used to build systems that detect unusual or anomalous behavior, including systems for intrusion detection, equipment malfunction detection and quality control.
Managed Business Intelligence (BI) can help to enable data-driven decision-making, and comes with tools for data modeling and simulation.
The adoption of AI in financial services is driven by the need to improve efficiency, reduce costs, enhance customer experience, and stay competitive. By leveraging the power of AI, financial institutions can transform their operations to better serve their customers.
Major AI use cases include: fraud detection and prevention, risk assessment and management, personalized recommendations, customer service, trading, underwriting, financial planning and advice.
Organizations in HCLS are adopting AI to improve patient care and outcomes, reduce costs, improve efficiency, and bring new treatments to market more quickly and efficiently. With AI, healthcare providers and life science companies can better serve their patients and customers.
Major AI use cases include: personalized medicine, medical diagnosis, medical imaging, treatment planning, population health management, drug discovery and development, clinical trial recruitment, automation of redundant tasks (e.g. document processing).
Manufacturers adopt AI to increase efficiency, improve quality, enhance decision-making, and facilitate product customization. AI helps to optimize production processes and reduce waste, leading to significant cost savings.
Major AI use cases include: predictive maintenance and analytics, quality control and assurance, production planning and scheduling, supply chain optimization, product customization, energy optimization.
Retailers and CPG companies adopt AI to gain a competitive edge by moving faster and making better decisions than their competitors. AI drives various efficiencies, from enhanced decision-making and better customer service, to cost reduction.
Major AI use cases include: customer service chatbots and personalized interactions, inventory management, fraud detection, supply chain management and optimization, pricing optimization, product development, marketing and advertising spend management.
AI improves transportation and logistics operations by optimizing vehicle routing and scheduling, predicting vehicle maintenance needs, and analyzing various sensor data. AI can help streamline operations, reduce costs, and improve service levels.
Major AI use cases include: route optimization and management, predictive maintenance for vehicles, warehouse optimization and management, demand forecasting, fraud detection, energy optimization.
AI helps energy and utilities companies to improve efficiency, increase reliability, and reduce costs. These advantages are essential in industries where margins are tight. AI also helps to identify new business opportunities and detect areas with potential for growth.
Major AI use cases include: predictive maintenance of equipment and systems, energy consumption forecasting and optimization, network optimization, fraud detection, personalized customer service.
AI has every tool for the media and entertainment industry to create better, more personalized and engaging experiences for audiences. It can help to increase ad sales by allowing for personalized, real-time ad insertions.
Major AI use cases include: personalized content recommendations, audience analytics, churn prediction, optimization of advertising and marketing campaigns, automatic content optimization for search, content creation.
AI enables genetics and biotech organizations to improve the efficiency and accuracy of research, increase profitability, and enhance the development and delivery of medical treatments. It can also dramatically reduce the risk of errors and oversight.
Major AI use cases include: at-scale analysis of genetic data, drug discovery and development, personalized medicine and personalized treatment recommendations, genetic diagnosis, clinical trial recruitment, disease diagnosis and prediction.
With AI, organizations can develop new products and services much faster and more effectively than their rivals. The adoption of AI in IT & software development can significantly improve processes, increase efficiency, and enhance the quality of products and services offered.
Major AI use cases include: AI-supported development of AI/ML products and services, AI chatbots for customer service, automated code generation and completion, automated testing, CI/CD-related automation, various data analytics use cases.
Managed Services help to automate the training, testing and deployment of ML models. This can include everything from building and testing models using various algorithms and frameworks, to deploying models to production environments.
Managed Services offer robust tools for monitoring and management of deployed models, including model performance monitoring and timely model updates.
Managed Services enable efficient communication, collaboration, and work sharing among Data Scientists and Data and ML Engineers, boosting performance and productivity.
Managed Services provide tools for efficient management and storage of data used to train and evaluate ML models. They also include tools for data wrangling, cleaning, and preprocessing.
Managed Services help ensure that ML projects adhere to compliance and security standards. They come with potent tools for data governance, and data privacy and security.
Managed Services provide tools and services for cost-effective cloud infrastructure management. These include tools for provisioning, configuring, and resource scaling.
Managed Services help optimize cloud costs by providing tools for efficient tracking and forecasting of resource usage. They also help identify opportunities for cost savings.
Managed Services provide useful tools and services for timely implementation of disaster recovery and backup plans, including tools for backup and recovery automation.
Managed Services ensure that cloud infrastructure is designed and built in accordance with best security and compliance standards. They offer tools for efficient monitoring and managing access to cloud resources.
Managed Services make it easier to deploy and manage various applications in the cloud. They come with all necessary tools for continuous integration and delivery (CI/CD).
Managed Services can help to automate and optimize business processes, with various tools for decision-making, process automation, and resource allocation.
Managed Services enable you to simplify the process of integrating data from multiple sources. They offer a variety of tools for extracting, transforming, and loading (ETL) data.
Managed Services help to ensure that data is secure and compliant, with tools for data access management and enforcement of specific data governance policies.
Managed Services provide tools and services for analyzing and visualizing data, including tools for handling reports, dashboards, and other data-driven insights.
Managed data pipelines make it easy to process and analyze data, with tools for data visualization, data mining, and machine learning.
Managed AI can be used to develop applications that recognize and classify images and speech. Such applications cover facial recognition, object recognition, and voice recognition.
Managed AI can help to build predictive models for forecasting future outcomes based on historical data. Such models can be used for financial forecasting, customer churn prediction, and demand prediction.
Managed AI can be applied to building applications that understand and process human language, including applications for language translation, text classification, and sentiment analysis.
Managed AI can help to build systems for detecting and preventing fraudulent activity, including credit card fraud detection, insurance fraud detection, and money laundering.
Managed AI can be used to build applications that personalize content and make recommendations based on user behavior and preferences, including applications for targeted advertising and product recommendation.
Managed AI can be used to build systems that detect unusual or anomalous behavior, including systems for intrusion detection, equipment malfunction detection and quality control.
Managed Business Intelligence (BI) can help to enable data-driven decision-making, and comes with tools for data modeling and simulation.
Provectus Managed Services
Full coverage of DevOps responsibilities within your organization, from infrastructure provisioning to SRE
Сloud-first data platform with a data lake ecosystem and data pipelines
for advanced analytics & BI
Managed MLOps platform for Data Scientists and ML Engineers or a fully managed end-to-end AI Solution.
How It Works
Provectus Managed Services can be provided as a customized or packaged* solution. Regardless of the chosen model, we start with a discovery workshop. Based on its results, we move forward with the pilot, scale, and managed solution phases.
*Covers the roadmap for all phases and provides up to 24/7 SLAs for the service
Program Deliverables
- IT operations efficiency assessment report
- Short-term plan to achieve quick wins
- Long-term assisted adoption roadmap
- Risk assessment and mitigation plan
The quality of Provectus Managed Services is determined by assessing such metrics as:
- Time to Resolution
- Time to First Response
- Percentage of Resolved Tickets
- Application Uptime
- CI/CD Infra Success Rate
- Infrastructure Uptime
- Add your metric here
Supported Tech Stack
Methods & Approaches
- GitOps
- Canary Deployment
- Continuous Integration (CI)
- Containerization
- Continuous Deployment (CD)
- Serverless Computing
- Continuous Testing (CT)
- 24/7 Monitoring & Support
Challenges that Provectus Helps You Resolve
Proactive management of operational risks in a complex regulatory and compliance environment
Quick access to the right combination of technical, operational, and strategic capabilities
Business cost-efficiency achieved through the latest technologies and industry-leading strategies
At-scale growth and agility, delivered by a dedicated team of AWS-certified engineers
Get Started Today
Reach out to the Provectus team directly, or continue with Provectus Managed Services at the AWS Marketplace!
