Overview
Provectus has experience deploying Generative AI and Machine Learning use cases on AWS with regulated healthcare, life sciences, financial services, and more enterprises. The Provectus approach is to dedicate a cross-functional AI pod of resources to accelerate the needed steps to migrate the workload to AWS, evaluate and refine models, and add new features to delight end users.
We encourage our customers to request participation and feedback from Business Leaders, Data, AI/ML Leaders, and IT professionals to increase use case adoption and business functionality in an effort to measure success criteria across the organization and help determine the return on investment.
Our client use cases range in complexity and data sizes, some examples:
AI Insurance Underwriting: turn complex documentation into meaningful insights that can be trusted to make high-value business decisions in minutes.
AI Auditor accelerates manual tasks like extracting insights from complex financial documentation in order to dramatically reduce the time, effort, and cost of the audit process.
Generative AI Assistant: surface insights from external and private data sources like contracts, support documents, collaboration platforms data, messaging apps, and task management systems to accelerate answers to essential questions.
Structured Finance: Extract insights from historical data, reports, and news on current market conditions, identify potential risks, and make better investment decisions.
The Provectus General Terms of Services, located at the following link: https://provectus.com/general-terms-of-services/ , governs the relationship between the parties for the duration of this scope of work.
Highlights
- Develop a roadmap for prototype to production deployment schedule
- Prioritize deploying features that will benefit users to encourage adoption across the enterprise
- Ongoing maintenance and support available to include new data sources and add customer-requested features
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