WHY MLOPS MATTERS:
Enables faster deployment, monitoring, and management of ML models in production.
Enhances collaboration across data science, engineering, and IT teams, reducing time to market.
Ensures model quality and consistency through continuous testing, validation, and monitoring
CURRENT CHALLENGES IN ML DEVELOPMENT:
- Only 1 in 10 ML models make it into production (Gartner, 2023).
- 85% of ML projects fail to deliver on initial promises (VentureBeat, 2023).
- Data scientists spend up to 45% of their time on model deployment rather than development.
HOW AUTOMATION TRANSFORMS MLOPS:
Ascentt’s MLOps solution simplifies and accelerates the end-to-end ML lifecycle, including:
- Data identification, exploration, and feature. engineering.
- Real-time model development, training, evaluation, and tracking.
- Implementing CI/CD pipelines for seamless deployment.
- Conducting batch or live inferencing and orchestrating ML lifecycle.
With up to 80% reduction in operational efforts, Ascentt’s MLOps automation drives significant efficiency gains, improved reproducibility, and scalable model management.
Contact us to learn how Ascentt can streamline your machine learning journey.
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