Thank you! We will get back to you soon.
Oops! Something went wrong while submitting the form.
Use Templates-as-Code to minimize configuration errors and reduce training preparation time by up to 40%.
Launch inference endpoints rapidly with prebuilt templates — cutting deployment cycles by up to 50%.
Improve team efficiency with standardized processes that reduce model onboarding and update time by up to 70%.
Use your existing cloud commitments to run workloads directly in your infrastructure and get the most value from your spending.
Meet enterprise-grade standards with built-in encryption protocols and certifications like SOC2 and HIPAA.
Roll out your solutions effortlessly across AWS, and soon Microsoft Azure — no vendor lock-in.
Streamline your delivery pipelines with built-in automation for training, deployment, and performance tuning.
Apply customizable role-based access controls aligned with your internal policies to protect your environments.
Tap into expert support services tailored to help your teams manage deployments and operations efficiently.
Automate every stage of your AI lifecycle — from deployment and training to inferencing and continuous improvement.
Eliminate manual tasks, reduce rework, and optimize infrastructure usage — cutting costs across your AI delivery pipeline.
Eliminate manual tasks, reduce rework, and optimize infrastructure usage — cutting costs across your AI delivery pipeline.
Integrate with your existing CI/CD, DevOps, cloud, and security stacks — without disruption.
Centralized dashboards give you full control over model performance, retraining needs, and deployment health.
Enforce governance, compliance, and security policies automatically across your AI infrastructure.
Overview:
To ensure reliable and repeatable model performance, OneX standardizes the entire machine learning workflow. This helps organizations reduce onboarding time and maintain consistency across multiple model iterations.
Integration Details:
• Standardizing the Workflow:
OneX creates repeatable, version-controlled templates to train and update models without manual intervention.
• Defining the Training Workflow (Supporting):
The solution ensures that every training job is configured uniformly, reducing variability.
Impact:
• Speeds up onboarding of new models or updates by 70%, significantly minimizing delays.
• Increases team productivity by reducing the learning curve and ensuring consistent operations.
• Enhances overall reliability across different projects and use cases.
Overview:
For organizations seeking to continuously improve their AI models, OneX integrates automated retraining and CI/CD-style deployment into existing ModelOps pipelines. This ensures that models adapt quickly to changing data and maintain high performance.
Integration Details:
• Integrating with ModelOps Pipelines:
OneX provides seamless integration with CI/CD pipelines, incorporating drift detection, monitoring, and automatic retraining triggers.
• Deploying Inferencing Endpoints (Supporting):
Automated endpoint creation optimizes resource allocation and enables real-time monitoring.
Impact:
• Enables continuous improvement with automated retraining and deployment pipelines.
• Enhances compliance by maintaining detailed audit trails of all pipeline actions.
• Ensures that inferencing endpoints are quickly and reliably deployed for production use.
Overview:
A client with an object identification platform can rapidly operationalize AI models using OneX. By automating both training and deployment, the solution dramatically reduces manual setup and speeds up production readiness.
Integration Details:
• Defining the Training Workflow:
OneX leverages Templates-as-Code in AWS SageMaker to configure training jobs—specifying data inputs, hyperparameters, and required infrastructure.
• Deploying Inferencing Endpoints:
The platform automatically creates scalable SageMaker endpoints for real-time or batch inferencing.
Impact:
• Cuts manual configuration errors and reduces training setup time by automating complex processes.• Accelerates training readiness, allowing models to be trained 40% faster.
• Cuts deployment time for inferencing endpoints by 50%, ensuring rapid production readiness.
Analytics Module
Collaboration Module
1 User
Up to 1,000 Events
Custom Reports
All in Starter Plan
2 Workspaces
5 Users
Up to 100,000 Events
Mobile App Tracking
