Trusted Monitoring at Scale,
Radical Performance Acceleration.

Trusted Models, Accelerated.

Vian H+AI Platform

Optimize, deploy, monitor, and manage more ML models – faster and at scale, to any cloud, on premises or to edge devices, with your existing teams and tools.

With Vian MLOps, our customers accelerate deployment of trusted, reliable models into production, and optimize model performance using commodity hardware, to drive down costs.

Comprehensive, Scalable ML Model Monitoring

Are ML Models Increasing Risks and Vulnerabilities for your Business, or Delivering Trusted Insights that Drive Transformational Decision-Making?

Here are seven critical capabilities to look for in an ML model monitoring solution.

The Need for a Unified but Modular Approach to MLOps

Deploy more models faster by abstracting away the complexity of fragmented tools and technologies across business, data science and IT teams. A unified but modular approach, leveraging an open, heterogenous platform enables customers to leverage end-to-end MLOps capabilities or simply use components, depending on need.

Deploy More Trusted Models into Production

Continuous Monitoring

Establish in real-time whether your ML models are behaving as intended. Is there drift or uncertainty? Has the data changed or the patterns changed? Find out in real-time at scale, across 100s or 1000s of models. With Vian Monitoring, reduce risks, increase governance controls and maximize visibility, trust and transparency of models throughout the model’s lifecycle. Monitor in real-time for drift, uncertainty, explainability, data quality, and more, to ensure the integrity and reliability of models over time.

Optimized Performance

Vian Performance Optimization maximizes ML model performance at the lowest cost, even on commodity hardware. As infrastructure costs skyrocket, we are enabling customers to accelerate the time-to-value of their ML models and helping them to realize the full potential of their AI and ML investments.

Operationalize ML Models at Scale

Model Onboarding

Onboard disparate models seamlessly and directly into our model registry where you can view all artifacts and prior experiments.

Model Validation

Perform uncertainty analysis to validate model data set and features, and validate model fit on training data.

Model Testing

Test model with new data for accuracy and performance before deploying into production.

Model Optimization

Accelerate model speed and throughput on your commodity hardware. No need for costly infrastructure upgrades.

Model Deployment

Eliminate friction with infrastructure and production challenges with automated provisioning and deployment at scale.

Model Inference

Serve inferences to requests from applications, business workflows, edge devices – in the cloud or on premises.

Model Monitoring

Continuously monitor models in production, set custom alerts for drift and performance decay, and gain deep insight to root cause with drill-down dashboards.

Model Rebuild/Retrain

Set triggers to automate pipeline retraining with new data, and redeploy updated models.

Continuous Monitoring

Auditability, Observability, Explainability
Pre deployment & Post deployment Risk Analysis
Continuous Monitoring

Enterprise Readiness & Scalability
Collaboration across all stakeholders & project phases
Simplifies model based business solutions as a service
Persona based UX abstracts complexity across multiple tools

H+AI for the Enterprise

Amplify the knowledge, experiences and decision making power of people in your organization.

Build trust, transparency, and accountability of AI to drive adoption at scale.

Deliver AI in a responsible way, reducing the cost, impact and risk of running AI systems.

A Human-Centered Approach to Drive AI Success

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