AI Resilience Lab

Decision Modeling needs retraining in time of extreme change

The best use of human judgement in these times of great change is to have our decisions informed by the facts as evidenced by verifiable events”

Today, we increasingly collect, organize and distribute data through digital platforms that support our processing of information and inform our queries, only to have hyphenated systems subject to inconsistencies process cognitively valuable information on the receiving end. FS.AI knows how we can build AI systems to ingest data to inform models, for end to end processes, that can readily adapt and learn from the new information that we are receiving and present it in a meaningful way based upon data governance which assures accuracy, timeliness and consistency.

This form of Cognitive Process Automation provides pre-trained and trainable models to enhance the cognitive input for executive and knowledge workers so that they can better perform specific tasks; while augmenting their analytical capabilities to navigate the increasing complexity to enable effective actions and to make informed judgements.

FS.AI Scaffolding™

Historically, risk modeling systems and business process management systems have been siloed to primarily support separate organizations. AI/ML driven cognitive process automation can update the current separate system models by scaffolding the end to end processes and data and recognize and correct the pain points in existing separated workflows by building trigger actions across organizations instead of building siloed platforms.  FS.AI Scaffolding framework cooperates existing platforms and data; helps build automation that can consume and govern vast amount of data; monitors and validates complex events; and make sense, supporting better understanding in a period of rapid change, by notifying you in a timely way to inform and to retrain your critical decision models.

Most AI transformations take 18 to 16 months to complete due to lack of specific solutions that they can point to and role model because a lack of analytics translators. These people bridge the data engineers and (data) scientists from the technical realm with the people from the business realm – risk personnel, marketing, supply chain, operations, Translators help ensure that AI applications address business needs and that adoption goes smoothly (HBR August 2019)

At FS.AI we are all translators, engaged in a Laboratory Environment with the customer to assure that the end result is the delivery of value through-out the engagement to a sustainable solution. We call this the AI Resilience Lab™ because it is where we create greater capability to respond to complexity and disruption, by recovering from the challenging situation with continuing a solution built for learning, testing and validation. We do this through the use of Game Theory which is integrated into our development sprints, where we gamify, as case exercises, the splits and joins of our processes and understand together, the business and flesh out technology pain-points in our operations model.

Our experience is that with this lab method and the consensus it creates, along with our AI Scaffolding™ framework we can deliver a minimum viable product within 3-4 months.

Ask to speak with one of our FS.AI translators, we enjoy bringing our experience, understanding, capability and enthusiasm to help you see how we can solve your decision modeling challenges by applying cognitive process automation.

Contact: info@finservai.com

In our AI Resilience Lab™ we utilize AI/ML tool kits to gain greater particiption, with our clients to provide, high-quality, on-line learning during our engagement through the following stages:
1) Workshop
2) Validation
3) Ingestion
4) Minimum Viable Product
5) Continuous Integration/Deployment

  • Access risk and effictive controls in proposed solution
  • Prepare for disruptions by identifying risk events
  • Build and implement system for model retraining
  • Promote a process of continuous improvement

We changed the way we operate so that you can that you can change the way you operate

AI Resilience lab environment and on-line learning experience serves to increase adoption outcomes through the use of simulation and Gamification

  • FS.AI and Client terms participate in delivering a solution widedata engineering modeling based on the client business problem
  • Simulation and Gamification techniques applied to Data Discovery
  • Machine Learning or Deep learning using cloud based enterprise-grade sandbox
  • 24×7 access to Q&A/Support through Discussion Forum; Leader Board and Learning Managment System