Responsible AI Platform

Deploy models with confidence

Responsible & explainable MLOps

  • A safe and responsible MLOps environment
  • Explain and understand AI decisions
  • Traceback how decisions are made
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Manage, Deploy, and Update

Easily deploy and update AI models

  • Deploy and update your AI models through simple steps
  • Collaborate using Deeploy’s UI, API, and Python SDK
  • Use API endpoints to integrate Deeploy into your application
Visual of the model decisions

Explainable AI

Explain model decisions to everyone

  • Support deployments with local and global explainers
  • Add custom explainers tailored to your end-users
  • Traceback explanations of historical predictions

Find out more about how we define explainable AI

Feedback loop

Improve model performance with human feedback

  • Facilitate interactions between AI and humans
  • Enable domain experts to evaluate predictions
  • Receive real-time feedback on models and predictions

Read how DDFinance uses feedback loops to improve their AI models

Visual of the feedback loop
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Integrations

Seamlessly integrates into your current workflow

  • Run Deeploy on your current cloud platform (AWS, GCP, Microsoft Azure)
  • Incorporate into existing code workflows (GitLab, CircleCI)
  • Receive notifications through Slack, mail and other channels

Audit trails

Reproduce and traceback decisions & explanations

  • Support for processes to comply with AI regulation
  • Trace and reproduce every change, prediction, explanation, and deployment
  • Ensure clear ownership of Deployments and Workspaces

Read how Coeo uses audit trails within their claim handling process

Audit trial in Deeploy
Monitor explainer from MyDeelpoy

Monitoring and alerting

Effectively monitor models, predictions and interactions

  • Constantly monitor model drift, bias detection, and performance
  • Define custom alerts for the metrics that matter to you
  • Easily discover the root cause of model degradation