INSIS AI provides machine learning-powered SaaS solutions and enables corporate-level AI transformation programs for insurance companies.
Every insurer holds unique historical data, domain knowledge and business goals. Depending on the needs of our clients, we build AI into an organization in two distinct ways: machine learning-powered SaaS solutions and AI professional services.
INSIS machine learning-powered SaaS solutions solve key insurance problems and automate legacy processes, while remaining completely customizable to every insurer’s unique use cases and datasets. Our first AI product, INSIS Cognitive Assistant, is an automated conversational customer assistance tool. Currently, it supports claim processing, quotation, and customer retention capabilities. Legacy insurance processes are augmented by intelligent messaging and IVR (interactive voice response) through digital assistants (e.g. Google Assistant), smart devices (e.g. Google Home), social messaging apps (e.g. Facebook Messenger, Viber), and telephony gateways.
INSIS AI enables long-term AI transformation programs for insurers, with the goal of creating tremendous enterprise and customer value. These long-term transformation programs may include professional services assisting insurer’s AI strategy and delivering impactful AI projects.
INSIS Cognitive Assistant is a pay-as-you-go license-based software solution that leverages state of the art machine learning models.
INSIS Cognitive Assistant is completely customizable to every insurers’ datasets and business goals. The AI team at Fadata works with our clients to build and test each machine learning model before deploying INSIS Cognitive Assistant into production.
1. Data collection and labeling
INSIS AI’s data labeling tools make it easy for internal teams to create labeled datasets.
2. Model development and training
Fadata AI team works with clients to determine the right project objectives, build and train models that achieve those goals.
3. Model deployment
Trained models are tested in real production environments. Fadata AI team will leverage the new data points coming through the data pipeline to improve the final deployed production models.
4. On-going support and training
After the final models are deployed, INSIS Cognitive Assistant continues to get smarter. INSIS Cognitive Assistant learns from new data, to continue improving the model performance.