Products

Customer Relations Management Artificial Intelligence (CRM AI)

DeLorean Artificial Intelligence (DAI) has developed a proven proprietary patent-pending technology, Customer Relations Management AI (CRM AI). CRM AI predicts if a deal will sell or not, if it will not sell where in the sales cycle will it die, and what is the next best action to move the deal to the next stage of the funnel and to win. Further, CRM AI allows sales to predict their revenue by quarter objectively. CRM AI knows which deals to pursue and those not to waste time. Our clients have seen a 7% increase in their sales with adoption of CRM AI.

DeLorean AI CRM AI

DeLorean AI created CRM AI, a full-scale end-to-end system of intelligence that has the ability to:

• Harvest all structured and unstructured data within a CRM funnel system into one database

• Perform horizon dataset establishment and profile (customer, deal, sales person, event) modeling

• Conduct real-time analysis of new deals, clients, and RFPs

• Predict which opportunities will win, fail or drop off

• Predict if a deal will not win, what are the next best actions to perform to increase the probability of winning

• Harvest and ingest external data sources to increase the refinement of the horizon dataset

In terms of the business, CRM AI allows the Sales and Marketing team of a client company to push the bell curve of the opportunities to the right. Basically, the results of using the CRM AI will allow leadership to decide which deals should be pursued, who should pursue them (based on hyperpersonalized outputs informed by client, deal, and salesperson information), and ROI. More winning deals will have more focus driving increased wins and close rates.

Product

Artificial Intelligence (AI) System of Intelligence (SOI) with real-time and predictive capabilities for sales pipeline and customer relationship management purposes; Customer Relations Management Artificial Intelligence (CRM AI).

Our Competition and Ecosystem

Currently, there are a number of Customer Relations Management Sales Funnels available in the market such as Sales Force Dot Com (SFDC), HubSpot, PEGA, Pipedrive, and INFOR. These software platform companies provide a service to manage the sales funnels of companies. Within these platforms’ sales personnel have the ability to track their contacts and deals from inception to either win or loss. The amount of data that they capture has evolved from their initial adaptation in the market. These platforms now give the ability to evaluate sales metrics through more basic and traditional analytics such as close rate and win rate and a greater line of sight for sales managers to monitor and evaluate their deal funnel at a high level and where each salesperson is in terms of performance. What is lacking is the ability to quantify if a deal is worth pursuing, will the deal win and if it will not win why and what can be done to increase the win and close rate.To this end a number of the CRM companies are in the process of trying to develop advanced data science and artificial intelligence tools to perform predictive analytics to assist their customers in managing customers, sales, deals and RFP’s. SFDC for example announced Einstein, their AI capability, which is still in development. These AI CRM personas are currently trying to predict if a deal will progress from one stage of the sales cycle to the next and are focusing predominantly on the analysis of structured data.

CRM AI Product Description

DAI has developed an SOI to integrate into a company’s CRM platform – Any company, any CRM platform. Specific focus to-date for clients has been to help achieve an enhanced level of accuracy in predicting sales cycle and end sales for varying products offered with different client populations. Further, DAI’s patent-pending proprietary technology has the ability to increase efficiency for field force sales.

CRM platforms such as Sales Force, Microsoft Dynamics, Hubspot, and Pega Systems are beginning to have the ability to generate insight as to how a sale will move from an individual phase of the sales cycle to the next, however, there is no clear capability to predict in real time how products or deals will perform with specific customers or clients.

DAI’s patent-pending CRM AI technology has the ability to predict in real time how a deal will perform in the future. Will it be sold? If it will not sell, what stage in the sales cycle will it fail? DAI’s technology also has the ability to infer why the sale will fail and which next best actions can be taken to increase the sale event or move the sale to the next phase of the cycle or successful end phase.

Our Patent Pending technology has the ability to connect to ANY CRM platform and complete the following:
1. Win/Loss Probability
2. Key Deal Progression Drivers
3. Next Best Stage Prediction
4. Final Deal State Prediction
5. Realtime Deal Directionality Prediction
6. Next best sales rep
7. Next best capability
8. Deal gap analysis
9. Deal conversion and intervention/recommendation

The CRM AI will allow for:

1. Increasing sales by 7% – current client experience
2. Increasing the population of deals that will win by excising deals not pursue
3. Choosing opportunities that have a higher probability for win and close rates
4. Shortening sales cycles
5. Reducing the cost of the win rate

Customer Relations Management Artificial Intelligence (CRM AI)

DeLorean Artificial Intelligence (DAI) has developed a proven proprietary patent-pending technology, Customer Relations Management AI (CRM AI). CRM AI predicts if a deal will sell or not, if it will not sell where in the sales cycle will it die, and what is the next best action to move the deal to the next stage of the funnel and to win. Further, CRM AI allows sales to predict their revenue by quarter objectively. CRM AI knows which deals to pursue and those not to waste time. Our clients have seen a 7% increase in their sales with adoption of CRM AI.

DeLorean AI CRM AI

DeLorean AI created CRM AI, a full-scale end-to-end system of intelligence that has the ability to:

• Harvest all structured and unstructured data within a CRM funnel system into one database

• Perform horizon dataset establishment and profile (customer, deal, sales person, event) modeling

• Conduct real-time analysis of new deals, clients, and RFPs

• Predict which opportunities will win, fail or drop off

• Predict if a deal will not win, what are the next best actions to perform to increase the probability of winning

• Harvest and ingest external data sources to increase the refinement of the horizon dataset

RTMCM AI generates real time predictions and interventive next best actions for care managers and medical directors to drive the most efficient treatment modalities to drive better healthoutcomes. The AI model produces an interactive module that is easily digestible for care managers and gives a simple risk based prioritized list of next best actions per member to drive increased health outcomes and decreased cost. RTMCM AI decreases per member per month (PMPM) costs as well as decreased medical loss ratio (MLR). DeLorean AI’s clients have decreased on average their PMPM for the sickest 1% by $100 ($1200 annualized) and on average $10 PMPM decrease ($120 annualized) for the other 99% of members. RTMCM AI has been implemented in major disease state management such as End Stage Renal Failure, Cardiovascular, COPD, Diabetes and Juvenile Asthma.

Product

Artificial Intelligence (AI) System of Intelligence (SOI) with real-time and predictive capabilities for sales pipeline and customer relationship management purposes; Customer Relations Management Artificial Intelligence (CRM AI).

CRM AI Product Description

DAI has developed an SOI to integrate into a company’s CRM platform – Any company, any CRM platform. Specific focus to-date for clients has been to help achieve an enhanced level of accuracy in predicting sales cycle and end sales for varying products offered with different client populations. Further, DAI’s patent-pending proprietary technology has the ability to increase efficiency for field force sales.

CRM platforms such as Sales Force, Microsoft Dynamics, Hubspot, and Pega Systems are beginning to have the ability to generate insight as to how a sale will move from an individual phase of the sales cycle to the next, however, there is no clear capability to predict in real time how products or deals will perform with specific customers or clients.

DAI’s patent-pending CRM AI technology has the ability to predict in real time how a deal will perform in the future. Will it be sold? If it will not sell, what stage in the sales cycle will it fail? DAI’s technology also has the ability to infer why the sale will fail and which next best actions can be taken to increase the sale event or move the sale to the next phase of the cycle or successful end phase.

Our Patent Pending technology has the ability to connect to ANY CRM platform and complete the following:
1. Win/Loss Probability
2. Key Deal Progression Drivers
3. Next Best Stage Prediction
4. Final Deal State Prediction
5. Realtime Deal Directionality Prediction
6. Next best sales rep
7. Next best capability
8. Deal gap analysis
9. Deal conversion and intervention/recommendation

The CRM AI will allow for:

1. Increasing sales by 7% – current client experience
2. Increasing the population of deals that will win by excising deals not pursue
3. Choosing opportunities that have a higher probability for win and close rates
4. Shortening sales cycles
5. Reducing the cost of the win rate

Our Competition and Ecosystem

Currently, there are a number of Customer Relations Management Sales Funnels available in the market such as Sales Force Dot Com (SFDC), HubSpot, PEGA, Pipedrive, and INFOR. These software platform companies provide a service to manage the sales funnels of companies. Within these platforms’ sales personnel have the ability to track their contacts and deals from inception to either win or loss. The amount of data that they capture has evolved from their initial adaptation in the market. These platforms now give the ability to evaluate sales metrics through more basic and traditional analytics such as close rate and win rate and a greater line of sight for sales managers to monitor and evaluate their deal funnel at a high level and where each salesperson is in terms of performance. What is lacking is the ability to quantify if a deal is worth pursuing, will the deal win and if it will not win why and what can be done to increase the win and close rate.To this end a number of the CRM companies are in the process of trying to develop advanced data science and artificial intelligence tools to perform predictive analytics to assist their customers in managing customers, sales, deals and RFP’s. SFDC for example announced Einstein, their AI capability, which is still in development. These AI CRM personas are currently trying to predict if a deal will progress from one stage of the sales cycle to the next and are focusing predominantly on the analysis of structured data.

Real Time Medical Care Management Artificial Intelligence (RTMCM AI)

The American healthcare payer market NEEDS the implementation of an AI that can source multiple data sources (structured and unstructured) to derive predictions (looking forwards) NOT analyses (looking backwards) to give payers, providers and patients better choices in care that reflect outcome, cost and regulatory compliance.  DeLorean Artificial Intelligence has developed a patent pending technology, Real Time Medical Care Management AI (RTMCM AI) that meets those needs.  Notably, RTMCM AI is a System of Intelligence (SOI) that develops mathematical profiles of patient journeys and treatment methodologies for specific pathophysiologies such as COPD, Coronary Heart Disease or Diabetes – sourcing information from claims, pharmacy, physician data, and external sources.

RTMCM AI is proactive at intervening and leveraging the insights generated to improve on disease prevention or progression, select optimal treatment, improve quality of care and longevity, and at the same time rationalize overall care management costs.

Real Time Medical Care Management AI is a full system of intelligence that harvests structured and unstructured medical and patient/member data internally and externally from the HC payer and categorizes medical risk level per member.  This health stratification is hyperpersonalized per member in real time.  RTMCM AI’s patent pending and proprietary technology then predicts what the next best action for a care manager to increase health outcomes and decrease costs per member.  Further, the AI model identifies members that are prone or precursor to a major pathophysiology allowing for management for disease onset.

The RTMCM AI Model produces the following results:

Predictions:

1. Real Time Member Health Directionality – based on primary diagnosis code
2. Member Health Trajectory (outcome & cost)
3. Disease Onset Management
4. Care Gap Analysis
5. Terminal Disease Journey Prediction & Mitigation
6. Drug Adherence Driver Analysis
7. Forecasted Cost & Utilization
8. Member Level Cost & Utilization

Interventions:

A. Next Best Care ActionB. Next Best Healthcare Provider ActionC. Provider Intervention RecommenderD. Medical Adherence

RTMCM AI generates real time predictions and interventive next best actions for care managers and medical directors to drive the most efficient treatment modalities to drive better healthoutcomes.  The AI model produces an interactive module that is easily digestible for care managers and gives a simple risk based prioritized list of next best actions per member to drive increased health outcomes and decreased cost.  RTMCM AI decreases per member per month (PMPM) costs as well as decreased medical loss ratio (MLR).  DeLorean AI’s clients have decreased on average their PMPM for the sickest 1% by $100 ($1200 annualized) and on average $10 PMPM decrease ($120 annualized) for the other 99% of members. RTMCM AI has been implemented in major disease state management such as End Stage Renal Failure, Cardiovascular, COPD, Diabetes and Juvenile Asthma.

Figure 1.: Example of how data is processed in real time resulting in a Care Management output so care managers have a prioritized and hyperpersonalized list of tasks per member to increase health outcomes and decrease costs.

Value Proposition:

• Improve health outcomes

• Optimized costs for treatment

• Drive a decrease of $100 PMPM cost

• Enable better managed care and help care management teams answer member questions in real time

• Improve payer brand positioning with both patients and physicians respectively

• Proactively manage payer approval for treatments

Approach Overview:

• Establish a System of Intelligence capable of text mining all available information regarding members and their medical history, in addition to unstructured data sources

• Perform risk analysis on member data and allocate risk scores based on the risk type (High Risk, Low Risk, Rising Risk)

• Identify the key features contributing to member transition

• Develop a practical demonstration of converting currently available unstructured data sources into usable structured format

• Analysis of treatment protocols and monitoring of member and patient risk scoring over time allows for deep machine learning analysis of existing episodes of care

• Provide hyperpersonalized care management recommendations per patient to decrease PMPM.  Allow insights per member for care managers to take specific tasks to increase health outcomes and decrease costs.

Why a better mouse trap:

It is our understanding that healthcare payer organizations routinely analyse their medical and pharmacy claims and associated data to ensure that HCPs provide the most efficient treatment modalities to generate best health outcomes.  We applaud this process, however, this process which is in the right directions, is actually looking “backwards” rather than looking to predict or looking “forwards”.  Our AI system of intelligence allows care management to make decisions that affect the member rather than make recommendations from lessons learned.Please join us on our journey……