Problem: Most start-ups move to the growth mode. It usually starts with customers on the plane while the engines need to be replaced while it’s still in the air. Using 3rd parties or “full stack” developers leads to that kind of security, stability, performance and scalability. Sometimes even using less than current architecture or outdated technology common with some 3rd party vendors. The company was operating with outdated legacy systems that limited its ability to adapt to market changes and meet customer expectations.

Solution: As part of a start-up, I advised the CEO and CMO on securing multiple rounds of funding from 5M to 25M with technical due diligence and led initiatives to re-engineer existing applications into fully cloud-based, mobile-ready platforms, with actionable data analytics. Led initiatives to build a new mobile-ready application for mobile devices, adding a designed data warehouse for customer and internal analytics, and migration from Delphi and static interface to AWS, Node.js, Lambda, .NET C#, S3, RDS, MySQL, React, HTML5, and CSS3, all modern technologies.

Problem: The company faced high operational costs and scalability issues with on-premise data centers while also moving to the cloud without using cloud-native technology, paying 15k a month for a Gb of data.

Solution: Developed and executed a cloud migration strategy, moving critical applications and data storage to a scalable cloud environment, which cut costs by 70% and enhanced business agility. Using relationships with AWS for well-built systems, and certified partners we were able to reduce costs, increase efficiency, and allow for future growth beyond the lift-n-shift strategy.

Problem: The company faced high operational costs and scalability issues with on-premise data centers.

Solution: Developed and executed a cloud migration strategy, moving critical applications and data storage to a scalable cloud environment, which cut costs by 70% and enhanced business agility.

Problem: The company faced high operational costs and scalability issues with on-premises data centers.

Solution: Developed and executed a cloud migration strategy, moving critical applications and data storage to a scalable cloud environment, which cut costs by 70% and enhanced business agility.

Problem: The existing IT infrastructure was rigid and costly, hampering scalability and innovation costing as much as a data center while only pursuing a lift n’ shift strategy that doesn’t actually reduce costs or increase inefficiency.

Solution: Transitioned to a cloud-native architecture, utilizing native cloud architecture and services from cloud providers, like Kubernetes and serverless computing, which improved scalability, reduced costs by 70%, and accelerated time-to-market for new features.

Problem: The company faced high operational costs and scalability issues with build vs. buy due to the evolution of growth company technology.

Solution: Developed and executed a cloud migration strategy, moved critical applications and data storage to a scalable cloud environment, and an application design to leverage cloud technology cutting costs more than 50% annually. Evaluated and negotiated cost-efficient PaaS platform to consolidate, and add orchestration, proactive monitoring, and support for data interchange. Evaluate best data warehouse solutions, designed and implemented scalable, real-time analytics using hosted PowerBI and Snowflake producing first-ever trust and actionable outcomes.

Problem: Legacy software was not compatible with modern operating environments, leading to increased security vulnerabilities and maintenance costs.

Solution: Led a project to rewrite and migrate legacy applications to modern, secure frameworks, reducing operational risks and maintenance costs by 70%.

Problem: Healthcare costs are rising, disparities in treatment plans and patient outcomes required options to improve outcomes, reduce costs, and determine best treatment plans with equal or better outcomes.

Solution: Led an effort to collect data across the payer/provider to an enterprise data warehouse, data integration, and analytics solution allow comparisons and unique analysis never seen before leading to the opportunity to help treatment plans, create reduced costs through treatments anticipated and provide. This cradle-to-grave aggregation of data allowed for a unified data system to create a centralized ability for reporting and analytics. This set the stage for our current era of machine learning and AI.

Problem: The company faced high operational costs and scalability issues with on-premise data centers.

Solution: Developed and executed a cloud migration strategy, moving critical applications and data storage to a scalable cloud environment, which cut costs by 70% and enhanced business agility while adding burst capacity using near-short staffing.

Problem: The company faced high operational costs and scalability issues with a stalled cloud migration with only a lift and shift.

Solution: Led hands-on technically architecting and leading an engineering team to use modern service-oriented architecture, security to develop a cost-effective, and scalable platform in AWS. Up-leveled team and added near-shore expertise to redevelop and consolidate using cloud-native technology; S3, RDS, mySQL, Serverless, Lambda, and Python. The results led to a secure, scalable and reduction in monthly ops cost 15k to 7k and developed strategic partnership with AWS for well-built system.

Problem: Decision-making was slow and often inaccurate due to reliance on disjointed data sources and manual analysis resulting in increased operational cost for marketing, patients, and overall operational cost.

Solution: Implemented a centralized business intelligence and analytics platform, enabling real-time data access and insights, which improved decision-making speed and accuracy.