Getting to Solutions
Working with stakeholders from the initial data strategy, we combine the latest technical advances, real-world expertise, AI engineering, and an understanding of business and data requirements to generate operational value.
We assist business leaders to understand and evaluate the essential areas for accelerating growth using their available and yet-to-be collected data coupled to potential AI use cases and data-driven strategies.
SFL Scientific takes an integrative approach, looking holistically at your entire business and all its important individual components to find these scalable prototypes. By engaging our data scientists and consultants with leaders and internal development teams, we can identify and streamline a path and develop a roadmap towards the most valuable business priorities in weeks.
Our consultants and data engineers specialize in developing on-prem, hybrid, and cloud architectures from data ingestion & ETL to modern compute systems leveraging GPU and AI Frameworks.
From DevOps to MLOps, our team provides management of your company’s information assets, real-time compliance monitoring using automated techniques, and recommendations on designing and setting up a proper data warehouse, lake, storage, and compute architectures.
SFL Scientific is the preferred service provider for NVIDIA, AWS, and Microsoft Azure, and partners with leading hardware and software vendors from Dell, HP, Cray to Pure Storage, Cisco, and many others.
SFL Scientific provides data science expertise across R&D, business, financial, and operational teams in each organization. We have deep knowledge in developing custom machine learning algorithms for specific business use cases. From engineering and data asset creation to data mining techniques that will help your company develop new technologies and drive revenue.
We provide custom development of business intelligence tools, with custom dashboards, aggregation, predictive analytics, and enterprise-level governance and security knowledge. We create tools that significantly impact businesses and the understanding of critical trends, allowing companies to pull levers to set goals to improve performance.
90% of AI models created are never put into production at large enterprises. This leads to most projects not showing the value that business leaders expect. SFL Scientific works with clients to 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.
We also help manage the machine learning applications making updates to the models, including testing and validation of new models. 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.
Our US-based team of data scientists, data engineers, and consultants are the cornerstone of our ability to serve our clients. Their high seniority and deep expertise in their respective fields enable us to deliver strategic insights and technical improvements, revolutionizing organizations with the intelligence pertinent to growth.
We’d like to work with you from modernizing legacy platforms to developing new AI solutions. Technology moves fast, let’s build sustainable solutions.