Managed AI Services

Facilitate and streamline end-to-end adoption of AI & ML across your organization with Provectus MSP

Managed AI:
A faster path to at-scale AI,

Provectus can help you handle huge amounts of high-quality data, a resilient infrastructure operating in the cloud, and an entire AI ecosystem. Our work includes developing and handling components for data governance, productionalization of AI & ML, model retraining and monitoring, and 24/7 support of AI/ML solutions in production.

Provectus’ Managed AI enables you to develop, enhance, and maintain AI/ML projects through Data Science, Machine Learning engineering, and DevOps. It ensures the speed, efficiency, and quality of any AI/ML work by filling talent gaps and reducing implementation risks.

What Is Managed AI?
Managed AI is an end-to-end service for managing AI workloads and a new approach to handling complicated, resource-intensive AI/ML tasks by third-party managed service providers. Managed AI enables companies to develop and deploy AI/ML solutions that deliver ROI, faster and at scale.

So far, only 12% of companies have advanced their AI maturity enough to achieve superior growth and business transformation. Managed AI offers your business a shortcut to gaining a competitive advantage with AI in your niche.

What Are the Benefits of Managed AI?
Continuously customize and enhance your AI solutions and ML models cost-effectively while maintaining high levels of security and compliance.
High Availability
Risk Management
Continuous Support
Managed AI with Provectus MSP
Provectus is an end-to-end, white-glove provider of Managed AI services. Our team of experienced DevOps, Data Science, Machine Learning and Data Engineering professionals can help your business meet its AI/ML needs at an affordable price, and with a strong commitment.
Engagement Model
Managed AI Scope

- Productionalization of your AI solution
- ML models quality SLAs
- System SLAs: uptime, latency, throughput, AWS costs
- Building and enhancing SRE measures
- 24/7 support of critical environments
- Model re-training
- Data, model, and concept drift monitoring

Managed AI Use Cases
Provectus offers an end-to-end solution and a fill-the-gaps solution, to help our customers succeed when they do not have the necessary resources or expertise to cover specific areas on the way to AI.
step 1
Managed MLOps

A complete, cloud-native MLOps platform enables you to iterate quickly and reliably from conception to production deployment of AI/ML use cases.

You will never have to build MLOps pipelines from scratch. Handle the ML production lifecycle and deliver ML models with reproducible pipelines faster and on a larger scale.

step 2
Managed ML Models

Development and maintenance of your ML models, from model building on labeled data and training code to model deployment to production, with further re-training and monitoring and supporting critical environments.

Ensure that the development, training, versioning, and deployment of ML models are managed at an adequate level.

step 3
Managed AI Solution

A comprehensive approach that can yet be customized based on the business needs, existing resources, and gaps.

Building industry-specific AI solutions, case by case, from first PoCs to production deployment and to scaling the solution across BUs, Provectus will account for required optimizations and your team’s feedback to ensure that every AI use case meets expectations and drives actual business value for your company.

Managed AI Provision Options
Baseline Deliverables

- All solution-related risks kept under control
- Dynamic roadmap with strategic and tactical goals
- Monitoring, incident response, and management
- Compliance (HIPAA, PCI, HITRUST, ISO 27001, SOC1, SOC2)
- Transparency and insights into the service performance and costs
- Regular reports and feedback loop

Ready to Kick Off?

Sign up for Acceleration Program and Build Your Own Solution Pilot

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Program Deliverables

  • Prioritized list of ML use cases with business KPIs
  • Use case feasibility report based on your data
  • Short-term path to prod to achieve quick wins
  • Long-term assisted AI/ML adoption roadmap
  • AWS funding eligibility assessment