Streamline Your AI Workflows With Our Operations Expertise
When AI models underperform, forecasting falters, and operations lose efficiency, missed opportunities and rising costs are inevitable, which forces stakeholders to lose trust and question technology investments that the business could benefit from.
At Scalefocus, we understand that developing and deploying AI solutions is just the first step. To ensure long-term success, it is essential to have a well-planned and efficient AI operations strategy. AI Operations services at our AppCare 360 operations center are designed to optimize AI workflows, ensure best DataOps practices, monitor and improve model performance, and reduce costs.
Core Services
Operations are what can make or break AI adoption in the long run. AI has a different life cycle than other digital solutions and needs a different approach, tools, skills, and, most importantly, a different mindset to be successful in achieving business goals.
Model Monitoring and Maintenance: Continuous monitoring and seamless updates of AI models for better accuracy and reliability at our AppCare 360 operations center.
DataOps: Ensures continuous quality, integrity, and security of AI models’ training and operating data.
Infrastructure Optimization: Optimization of the underlying infrastructure to support AI workload demands.
Feature Management: Seamless management of model features using dedicated feature store solutions.
Scalefocus’ dedicated MLOps teams streamline the machine learning lifecycle, from data preparation to model deployment and operations.
Model Selection/Customization: Machine learning model selection, fine-tuning, using industry-standard tools and technologies.
Model Deployment: Automated pipelines for machine learning deployments in production environments to ensure scalability, reliability and uninterrupted operations.
Model Monitoring: Continuous monitoring of machine learning model performance, detecting data drift and concept drift.
Model Maintenance: Regular updates and fine-tuning of machine learning models to adapt to changing data distributions and business requirements.
Scalefocus has vast experience running and supporting AI workloads in various environments.
Cloud: AI models deployment and management on cloud platforms such as AWS, Azure, Google Cloud, and IBM Cloud.
On-Prem: Deployment and management of AI models on-premises, using containerization, virtual machines, or bare-metal infrastructure.
Edge AI: Deploying and managing AI models on edge devices, such as IoT sensors, cameras, and other specialized hardware.
Our AI Operations Process
Our team follows a structured approach to ensure successful AI operations that deliver results on time
and on budget.
AI Operations Industry Expertise
Our team brings extensive experience in designing and implementing AI operations strategies for various use cases across industries.
Fintech
- Risk Management
- Fraud Detection
- Portfolio Optimization
Healthcare
- Clinical Decision Support Systems
- Medical Imaging Analysis
- Patient Monitoring Solutions
Industrial Automation
- Predictive Maintenance
- Quality Control
- Supply Chain Management
Why Scalefocus
Scalefocus’ unique approach to AI operations has been pivotal for our projects’ success.
Here is what sets us apart:
Client Success Stories
From enabling real-time consumer insights to revolutionizing knowledge management and agile staffing, our AI solutions help clients achieve greater efficiency, accuracy, and innovation. Leveraging advanced AI technologies and MLOps expertise, we empower organizations to accelerate business outcomes in data-driven environments.
AI-Enabled Consumer Intelligence for US Technology Leader
AI-Powered Solution for Efficient Knowledge Management
