Predera introduces AIQ, an automated end to end MLOps solution for machine learning teams to drastically cut down on the challenges faced today in building, deploying and managing machine learning models.
AIQ provides a command center view of all your ML models in one place to improve the visibility and decision making for leadership.
Build, Deploy and Monitor Machine Learning Projects with minimum effort and low cost by automating end to end MLOps solutions.
Machine Learning Solution for Data Scientists
Onboard any Data Science project in minutes with AIQ Workbench. Your data scientist can kick start model building by spinning notebook servers, connecting to git, and track modeling activities within the team.
AIQ Workbench provides the ability to version control experiments with no coding effort. Most other ML platforms require additional code to log metadata around your features and models. This often clutters model code base with too many log statements making it less-readable and manageable (‘code spaghetti’). With just 2 lines of code, AIQ empowers ML models to log all the required features. Never lose another AI/ML experiment, artifacts, metrics, lineage. We collect it all – seamlessly, agnostic to the programming language.
AIQ Workbench fosters team collaboration with the visibility into Machine Learning projects not just for Data Scientists but also business leaders to make affirmative decisions based on ML outcomes.
Automated MLOps for ML Engineers
Single-click deployment to turn Machine Learning Models into scalable APIs? Use AIQ Deploy.
Deploy Machine Learning Models to Production within minutes with reusable CI/CD templates and automatic scaling of computing resources.
Deploy Machine Learning models to any cloud, on-prem or hybrid environment by a single click with templates for complex deployments like A/B testing, graph, transformer, TensorFlow along with pre-, and post-, deployment, and validation steps.
And when it’s time to switch to your compute environment of choice, simply log into AIQ Deploy and redirect your models to it. No more vendor lock-in!
Unified Monitoring Dashboard for ML Projects
AIQ Monitor (in beta) provides a unified dashboard enforcing collaboration among Data Scientists, MLOps team, and Business to collectively monitor model performance and resource consumption to reduce cost and at the same time improve efficiency of machine learning models.
Monitor model performance and resource utilization along with bias and data drift at real-time in a reliable, scalable and explainable way so your Data Scientists spend less time debugging.
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