AWS
AI & Machine Learning Solutions

Build intelligent applications and extract actionable insights from your data with our expert AWS AI/ML implementation services

Vizio’s AWS AI/ML Expertise

Vizio Consulting specializes in transforming business challenges into AI-powered solutions through expert AWS implementation. Our team of certified AWS ML specialists brings both technical expertise and business acumen to deliver AI/ML implementations that drive tangible results.

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Our Comprehensive Approach

Why Choose Vizio

Vizio enables organizations to cut storage costs by using smart tiering that adapts to changing data access needs.

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Artificial Intelligence //
The impact of AI on the evolution of future technologies. //
Artificial Intelligence //
The impact of AI on the evolution of future technologies. //
Enterprise-wide reporting //
regulatory compliance //
Cross-functional analytics //
AWS //
Our implementation expertise spans the full spectrum of AWS’s industry-leading AI and machine learning technologies

Core AWS AI/ML Services

Amazon SageMaker Amazon Comprehend Amazon Rekognition Amazon Personalize Amazon Forecast

Amazon SageMaker

A fully managed service that enables data scientists and developers to quickly build, train, and deploy machine learning models at scale. Vizio’s implementation expertise helps you leverage SageMaker’s automation capabilities and built-in algorithms to accelerate your ML initiatives.

Amazon Comprehend

Platform: Natural Language Processing (NLP)
A managed NLP service using machine learning to extract insights and relationships from unstructured text, enhancing customer experiences and business intelligence.

Amazon Rekognition

Platform: Computer Vision & Image/Video Analysis
Adds image and video analysis to your applications using deep learning. Identifies objects, people, text, scenes, activities, and detects inappropriate content.

Amazon Personalize

Platform: Real-Time Personalization
Delivers individualized recommendations for users in real time using machine learning. Allows building recommendation systems for diverse digital experiences.

Amazon Forecast

Platform: Time Series Forecasting
Build accurate forecasting models using machine learning to predict business outcomes. Combine historical data with related external factors to generate precise forecasts for inventory, demand, and financial planning.

We follow a proven methodology to deliver successful AWS data warehouse implementations:

Our AWS AI/ML Implementation Process

01
Business Discovery
02
Data Assessment
03
Data Preparation & Engineering
04
Model Development & Training
05
Deployment & Integration
06
Monitoring & Optimization

PHASE 1: BUSINESS DISCOVERY & DATA ASSESSMENT

The process begins by understanding your business objectives and identifying suitable ML use cases that deliver meaningful impact. Data scientists and ML engineers perform a thorough assessment of your data landscape, evaluating quality, accessibility, and suitability for machine learning applications.

  • AWS Glue – Data catalog and ETL
  • Amazon S3 – Data lake storage
  • Amazon Athena – Data analysis and querying

PHASE 2: DATA PREPARATION & ENGINEERING

Raw data is transformed into ML-ready formats through cleaning, normalization, and feature engineering. Data engineers utilize AWS services to build scalable data pipelines, ensuring consistent, high-quality data for downstream use.

  • AWS Glue DataBrew – Visual data preparation
  • SageMaker Data Wrangler – Data preprocessing
  • SageMaker Feature Store – Feature management

PHASE 3: MODEL DEVELOPMENT & TRAINING

ML specialists select optimal algorithms and model architectures for your specific use case. Leveraging Amazon SageMaker and other AWS ML services, models are developed, trained, and tuned for exceptional accuracy and performance.

  • SageMaker Studio – Integrated ML development environment
  • SageMaker Training – Scalable model training
  • SageMaker Experiments – Experiment tracking

PHASE 4: DEPLOYMENT & INTEGRATION

Trained models are deployed into production environments using AWS’s scalable infrastructure. The process ensures seamless integration with existing systems, creating secure, efficient inference endpoints for real-time or batch predictions.

  • SageMaker Endpoints – Real-time inference
  • SageMaker Pipelines – MLOps automation
  • AWS Lambda – Serverless integration

PHASE 5: MONITORING & OPTIMIZATION

The commitment extends beyond deployment. Comprehensive monitoring systems are implemented to track model performance, detect data drift, and ensure optimal operation. Continuous refinement and retraining maintain and improve accuracy over time.

  • SageMaker Model Monitor – Performance tracking
  • Amazon CloudWatch – System monitoring
  • AWS Cost Explorer – Cost optimization
Vizio translates AWS AI/ML capabilities into tangible business outcomes through three key areas

Business Impact

Intelligent Decision Making

36% improvement in forecasting accuracy and 60% of decisions driven by data.

Operational Efficiency

27% reduction in manual processing and a 31% increase in automated operations.

Enhanced Customer Experience

45% increase in customer satisfaction and an 18% growth in the customer base.
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Data Accessibility
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Data Governance
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Implementation Considerations

Key factors to consider when implementing AWS AI/ML solutions in your organization:

Key factors to consider when implementing AWS AI/ML solutions in your organization:

Implementation Considerations

01

Build vs Buy

02

Infrastructure Architecture

03

MLOps Strategy

05

Data Quality & Preparation

06

Data Accessibility

04

Data Governance

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Business
Discovery & Data Assessment

  • Business objective alignment
  • Use case prioritization
  • Data quality assessment
  • Technical feasibility analysis

Future Outlook

Stay ahead of the time with Vizio’s forward looking approach towards AWS AI/ML innovations 

Generative AI is transforming how businesses create content, generate code, and engage with customers. Vizio helps you adopt AWS tools like Bedrock and SageMaker to build scalable, intelligent experiences that drive innovation and efficiency.

Efficient machine learning depends on strong MLOps. Vizio enables you to automate your ML lifecycle using AWS services such as SageMaker Pipelines and CloudWatch—driving faster deployment, better governance, and long-term model performance.

Trust is vital in AI. Vizio ensures your models are ethical, explainable, and secure by applying AWS tools like SageMaker Clarify and IAM policies—helping you meet compliance and build user confidence.

Through strategic AWS partnerships and ongoing innovation, Vizio ensures your AI/ML solutions stay modern, scalable, and future-ready—empowering your business to grow with the pace of change.

Conclusion

Transform Your Business with Vizio’s AWS AI/ML Implementation Services

  • AI-powered solutions
  • expert AWS implementation
  • machine learning solutions
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