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Cloud analytics and AI
Infuse cloud-enabled, AI/ML into your business apps to make them smarter
Greater insight into business performance can create a competitive advantage. Artificial intelligence/machine learning (AI/ML) can provide that insight. Through the use of smart applications (SmartApps), Deloitte delivers the custom AI/ML solutions companies need to embed and operationalize AI/ML into their business applications and deploy them—at scale—with cloud native flexibility to gain deeper insights, improve business outcomes, and engineer advantage.
Delivering smart applications
Our approach helps you operationalize AI/ML models, deploy and scale features with cloud cloud native flexibility, and enhance the user experience with advanced interactive dashboards and continuous learning. Our SmartApps framework provides a full array of services, from suitability analysis to proof of concept, to AI/ML model and application building, to ongoing maintenance and operations.
Assets and accelerators
To accelerate application delivery, we employ a toolkit of Deloitte assets and accelerators including:
- SmartApps Labs
- AI/ML Remediation Diagnostic
- ML Ops Services Setup
- Ongoing Cloud Managed Services
These tools help us rapidly assess your needs; determine the optimal path to implement AI/ML models; and optimize the ongoing training, maintenance, and operations of your cloud native, AI/ML-infused business applications.
Impact of smart applications
The impact of implementing Deloitte’s SmartApps approach is clear. SmartApps helps:
Infuse intelligence into applications.
Infusion of prebuilt or custom AI/ML models into business applications for deeper insight and improved business performance.
Enhance the customer experience.
Continual retraining of integrated AI/ML models and faster release of new application features using the SmartApps framework.
Enable industry cloud use.
Ability to leverage industry clouds faster and more effectively by infusing AI/ML capabilities into industry cloud capabilities and toolboxes.
Combine app model deployment and learning.
Simultaneous deployment and continuous training of integrated AI/ML models at the same time, for consistent improvement.
Scale with cloud native services.
Use of rigorous software design principles to accelerate development and scaling of robust business applications.
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