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Model Deployment

Realize your AI model's potential

Showing the value of that AI model rests with deployment. Model Deployment or MLOps helps to deploy, monitor, manage, and govern machine learning models into your production environments.
Model Deployment

Overview

SFL Scientific can easily deploy your custom machine learning projects on modern production infrastructures such as Kubernetes on any cloud or on-premise system while maintaining and enforcing governance related to your solution.

Our Approach

Our clients seek scalable, automated processes supported by validated, custom AI and analytics to improve human decision making and reduce manual labor, often in critical and regulated environments.

With advances in digital data sources, cloud, infrastructure, and data distribution, by applying our data science approach, we deliver enhanced risk identification, solution integration, and a full assessment to develop a comprehensive roadmap and a successful technical strategy.

01 Functional and business specifications requirements mapped to technology.
02 Training dataset assembly, quality, and pre-processing pipelines.
03 Pilots to assess performance and future model accuracy.
04 Model augmentation, tuning, and validation in real-world environments.
05 Integration and scaling to production for end-user consumption.

Our Custom Strategy

Model Deployment

Easily deploy machine learning projects written in modern languages and frameworks, on modern production infrastructures such as Kubernetes on any cloud or on-premise system.

Monitor

ML-based applications for performance issues with ML-centric capabilities like data drift analysis, model-specific metrics, and alerts. Provides proactive management and timely updates that don’t waste resources and ensure continued application performance.

Manage

The dynamic nature of machine learning applications with the ability to frequently update models, including testing and validation of new models. Update models on-the-fly while continuing to serve business applications.

Governance

Enforce governance policies related to machine learning models and capture the data that is required for strong governance practices in machine learning operations management, including who is publishing models, why changes are being made, and which models have been deployed over time.

Hear From Our Clients

The ability to couple large medical imaging datasets from our leading healthcare clients with the exceptional computational performance of the DGX GPUs and novel deep learning model development from SFL Scientific has been critical in building our platform of AI image classification applications.

Jim Havelka, CEO, InformAI

On developing novel artificial intelligence solutions for defense applications: “SFL Scientific is a reliable partner who brings great minds to the hard problem sets, delivering on custom and state of the art Artificial Intelligence solutions.

Todd Borkey, Chief Technology Officer, Alion Science & Technology

Trusted by Leading Organizations Worldwide

We enable organizations to utilize their data, automate processes, innovate, and operate more efficiently.

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