AWS SageMaker Consulting Company Building Enterprise-grade ML Apps

AWS ConsultingAWS Partner

Softweb Solutions can help from strategizing ML implementation to developing ML models using SageMaker to integrate into business systems. Our value-driven AWS ML solutions use features such as computer vision, video analytics, speech recognition and language analysis to predict, build, and deploy ML apps.

  • Design custom ML architecture as per your business use case
  • Integrate your current business systems
  • Build recurring training pipelines with SageMaker APIs
  • Monitor and improve your ML models for seamless operations

Our AWS SageMaker Services

Consulting and StrategizingWe build an impact-driven ML strategy that aligns with your business goals and make a roadmap for AI success with definite KPIs.
ML Model DevelopmentOur ML experts leverage AWS SageMaker to build custom machine learning solutions across different lines of business.
ML ModernizationWe migrate your existing databases/apps to the cloud without downtime. With feature-rich modernization, we maximize Amazon SageMaker services to develop the self-learning ML models.
ML Model ManagementWe monitor model performance, mitigate risk and build effective ML systems in a multi-faceted AWS cloud environment.

Looking for impact-driven AI strategy that supports with your business goals?

Benefits of AWS SageMaker Services

AWS rich algorithm library

AWS rich algorithm library

Pay as you use model

Pay as you use model

Make ML more accessible

Make ML more accessible

Prepare data at scale

Prepare data at scale

Accelerate ML development

Accelerate ML development

Streamline the ML lifecycle

Streamline the ML lifecycle

Features Of AWS SageMaker

Amazon SageMaker Data WranglerOur ML team transforms your unstructured data into features by using built-in data transformation.
Amazon SageMaker ClarifyWe provide clarity in bias detection during and after the training to enhance the data models.
Amazon SageMaker Ground TruthOur ML specialists label data to create high-quality training datasets quickly at reduced costs.
Amazon SageMaker DebuggerOur experts assist in detecting and debugging errors in the model prior to the deployment of the model.
Amazon SageMaker Features StoreWe reduce repetitive data processing and curate work to convert raw data into features for training ML algorithms.
Amazon SageMaker Built-in NotebookOur team leverage built-in Jupyter notebooks for building and sharing codes and equations.
Amazon SageMaker PipelinesOur ML experts create a workflow for the end-to-end machine learning model, from structuring, training to deployment.
Amazon SageMaker ExperimentsWe allow to organize, track, compare and evaluate multiple machine learning experiments and model versions.

Hire AWS SageMaker Developers

Hire our AWS certified machine learning specialists to develop and deploy ML models. By the virtue of our ML experts, solve your complex business challenges supported by business data intelligence, processing and workflow orchestration to create high-quality training datasets data challenges. We understand the nuances of AWS SageMaker and can help you with superior machine learning models as per your various business use cases.

SageMaker
Portfolio

Ensure efficient packaging with AWS SageMaker for pharma company

A pharmaceutical manufacturer transformed its packaging quality control checks and QA testing with AWS solutions. Our AWS SageMaker developers created a visual analytics solution that detects inefficiencies in packaging processes and quality assurance methods. Learn how Amazon SageMaker:

  • Enables companies’ developers to build, train and deploy ML models efficiently.
  • Supports custom ML solution development for improved predictive analytics.
  • Analyzes every package and assigns a label using ML model.
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500+

Employees
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600+

clients
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25+

Products and solutions
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1400+

Projects

Why choose us

AWS SageMaker offers an extensive set of machine learning (ML) and artificial intelligence (AI) capabilities to meet business needs. Softweb Solutions can build, train, and deploy ML models quickly with Amazon SageMaker services, improve productivity, enhance customer experience, optimize business processes and scale up innovation.

  • ML development lifecycle in one integrated environment
  • Add intelligence to business applications
  • Automate data extraction and analysis
  • Forecast future values and detect business anomalies

Creating high-performance and low-cost ML models at scale

Our AWS certified ML experts automate MLOps practices across your organization