Steven Shillingford is President and CEO of DeepSee.ai, a Knowledge Process Automation (KPA) platform to mine unstructured data, operationalize AI-powered insights, and automate results into real-time action for the enterprise. He is the creator of the Knowledge Process Automation industry category, delivering AI-powered automation and productivity via easy to deploy, cloud-based business flows for critical business operations in the Capital Markets and Insurance verticals. He has led several startup enterprises, building cloud-scale platforms and helped found a successful cybersecurity platform for big data analytics supporting network surveillance systems for a range of verticals, from intelligence agencies to Fortune 500 companies.
Steven Shillingford’s LinkedIn: linkedin.com/in/steve-shillingford
Steven Shillingford’s Website: https://deepsee.ai/
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Here’s the timestamps for the episode:
(00:00) – Introduction
(02:31) – Innovation Cycles used to be about features, but now consumers and enterprises look for innovation around processes
(06:53) – Using AI to surface the information that is most useful through a configurable tool bias towards action.
(13:52) – NLP to support different tools for different types of business problems inside the enterprise
(16:29) – A hybrid approach where people need interaction to lead us to “enhanced accelerated productivity”
(22:26) – Reducing processing time to offload a non-human optimized work to the machine, keeping Computers working on behalf of the humans
(23:42) – Operationalize data science and the innovation that comes from AI around outcomes to achieve knowledge, reduce cost, mitigate risk and improve customer satisfaction, not only in capital markets or insurance, but across a number of industries
(26:53) – A platform that matches unstructured data in different business models, but same processes. Automation of checkpoints by a machine using the Deepsee platform as in capital markets
(30:27) – Helping research get faster results. Streamlining paper processes to innovate in new therapeutics, new vaccines, medical supplements and medications, as well as the technology used for blockchain
(33:50) – More than document digitization it’s document and data analysis, preserving data provenance across all actions to build trust through transparency and achieve wide-scale adoption.