United States
Hi, I’m R. Michael Merritt — a founder, AI product leader that specializes in the strategic application of artificial intelligence across machine learning, generative AI, computer vision, and statistical learning, bringing these capabilities together to design scalable, human-centered products. Over the past decade, I’ve led AI-driven transformation initiatives across Fortune 50 organizations including Google (Vertex AI), IBM Watson, Disney, and Humana, operating at the intersection of product strategy, enterprise adoption, and advanced analytics. Today, I’m the Founder & CxTO of my fourth startup, Satori Ai, an AI-powered personalization platform reimagining how consumers understand, manage, and interact with their physical and digital worlds—starting with fashion and extending into broader lifestyle and commerce domains. Satori is being built with the rigor of both enterprise AI and venture innovation, supported by my membership in the University of Chicago’s Polsky Center for Entrepreneurship and Innovation, where I engage in founder programming, mentorship, and applied commercialization pathways. At Satori Ai, we’re building a privacy-first personalization platform that combines multimodal AI, intelligent ranking systems, and real-time consumer signal modeling. Our work spans wardrobe intelligence, sustainability insights, consumer graph modeling, and emerging experiences such as AR-assisted personalization and embedded commerce, all focused on transforming raw data into clarity, confidence, and action—without compromising trust or privacy. My work as a founder extends the skill sets: • Designing consent-driven, privacy-first personalization systems • Applying financial engineering principles to personalization economics • Building ML systems that address real cold-start and sparsity challenges • Translating complex AI architectures into intuitive, emotionally resonant user experiences, including spatial and AR-enabled interfaces I bring a strong foundation in quantitative finance and data science, with advanced training and matriculation into programs at Carnegie Mellon University (Machine Learning, GenAI & Data Science), Quantitative & Financial Engineering, the Wharton School of Business, UT Austin, and the University of Illinois Urbana-Champaign, alongside hands-on experience in DevOps, MLOps, and production-grade AI systems.
Building Sartori AI, a multimodal Wardrobe Intelligence System that transforms how people interact with clothing—from fragmented browsing to intelligent, confidence-driven outfit decisions. Sartori operates beyond traditional recommendation engines by understanding how garments work together across context, preference, and real-world use. The platform combines computer vision, LLMs, and advanced recommendation systems to generate personalized outfit recommendations, wardrobe insights, and purchase guidance. Platform capabilities include: * Digital wardrobe inventory & outfit generation * Context-aware styling (season, occasion, climate) * AR/virtual try-ons, body-scanning, and smart mirror integrations * Personalized “lookbook” and e-commerce decision support Key impact: * Improved new-user recommendation relevance by +27% (cold-start + seasonal modeling) * Reduced load times by 65% via multi-threaded embedding pipelines * Migrated to modular, cloud-ready architecture (99.9% uptime) * Accelerated release cycles from 7 days → 36 hours (CI/CD integration) * Drove 2.3× increase in session duration through UX improvements * Generated 500+ pre-launch waitlist users Tech stack: Multimodal embeddings (CLIP), vector search, LightGBM reranking, FastAPI microservices, GPU-aligned inference architecture. Sartori is being developed within leading AI and startup ecosystems, including NVIDIA’s AI ecosystem, Google for Startups Cloud Program, MongoDB for Startups, and the Polsky Center for Entrepreneurship and Innovation. Vision: Build the intelligence layer for fashion—enabling digital wardrobe twins, real-time outfit decisions, and smarter, more personalized consumption.
SaaS, PaaS | B2B, B2C, MTM | FinOps, FinTech, AIOps, MLOps, HealthTech, MarTech, CRM, OMS, DMP, DMKT, EMM, CMP Led IBM Watson Health, Marketing, and Commerce portfolios with a focus on generative AI innovation and platform modernization. Partnered with startups to deploy AI-native copilots in healthcare, reducing readmissions by 12% across a dataset of 300M+ patients. Scaled AI-driven marketing and content platforms, tripling lead quality and cutting production time by 30%. Championed agile product strategy, improving roadmap incorporation rate to 85% and driving ARR up by 11% via product-led onboarding. Directed cross-functional teams with dual-track agile, raising alignment scores from 6.5 to 8.5. Introduced ethical AI practices, improving model resilience to adversarial attacks from 60% to 95%. Key Results: • AI NLU redesign → +32% CSAT, -15% churn • mAP (vision AI) → from 0.65 to 0.85 • Infrastructure savings → -22% YOY • Model training time → 5.4x faster
Drove strategic AI product initiatives for Watson Health and Marketing portfolios. Applied Jobs-to-Be-Done and outcome-based roadmaps to define growth-oriented priorities. Launched NLP-powered Watson NLU and multilingual ASR tools. Enhanced IoT-driven predictive analytics for Watson Supply Chain, enabling autonomous demand planning. Boosted model performance with rigorous A/B testing and optimization. Cut defect rates from 15% to 3% and scaled weekly production releases from 2 to 10. Elevated F1 score for NLP sentiment models from 0.75 to 0.92. Key Results: • Speech/NLU → +32% CSAT, -15% churn • IoT demand forecasts → real-time insights • Model tuning → +440% training speed
Led end-to-end PLM for AI-first healthcare and commerce solutions, including Watson Health Imaging, Clinical Trials Matching, and Watson Order Management. Executed Lean Analytics, A/B testing, and JTBD frameworks to drive customer-centric releases. Introduced computer vision for clinical workflows and AI-assisted 3D reconstructions. Led feature flag-based rollouts and proactive anomaly detection—cut false positives from 10% to 2%. Key Results: • Vision model precision → mAP +30% • Analysis time → -35–83% • DevOps throughput → 5x deployment rate
SaaS, API | B2B | HS, HIT, HRC, HCS, AIA | HealthTech, RegTech, CMP, DMP Led the transformation of MedHOK Care Management (now CareProminence), a cloud-based healthcare platform under the prestigious Hearst Health network. Focused on scaling technical excellence, driving API-first innovation, and ensuring full compliance with stringent healthcare regulations to position MHK as a leader in health tech solutions. Key Responsibilities: • Architected API-First Ecosystem: Spearheaded the development of scalable, secure API frameworks, enabling seamless interoperability across healthcare systems and accelerating partner integrations by 40%. • Advanced Product Roadmapping: Defined and executed a forward-looking, data-driven product roadmap, embedding predictive analytics and machine learning capabilities to enhance platform intelligence. • Healthcare Compliance at Scale: Led the integration of cutting-edge privacy and security features aligned with HIPAA and CMS guidelines, setting a benchmark for regulatory excellence in cloud-based healthcare solutions. • AI-Driven Workflow Automation: Introduced AI-based automation to streamline clinical workflows, reducing processing times by 30% and improving overall care management outcomes. • Data-Driven Product Insights: Built and operationalized advanced analytics dashboards, enabling real-time monitoring of product KPIs and user engagement metrics for agile decision-making. • Scalability Initiatives: Designed scalable infrastructure strategies to support the onboarding of enterprise healthcare clients, increasing system reliability and uptime to 99.5%. Notable Achievements: • Revenue Acceleration: Delivered 18% revenue growth through strategic product innovation and entry into new healthcare markets. • Market Expansion: Orchestrated technical strategies to drive a 28% increase in product adoption rates, ensuring solutions met the needs of a rapidly evolving healthcare landscape.
SaaS | B2B, B2C | HS, HIT, HRC, HCS, AIA | DMKT, E-Comm, DAT, CRM, DSTech, Responsible for advancing healthcare technology innovation at Centene, focusing on SaaS, B2B, and B2C platforms development, across Health Services, Health Information Technology, and AI applications. I led the maturity of digital marketing, the e-commerce division, data analytics, CRM teams, and decision support solutions, aligning these initiatives with Centene's strategic goals and needs of our 28 million members. The successfully implementation, resulting with an AI-driven telehealth platform for efficient scheduling and improved care access, designed with a personalized wellness program to boost user engagement, and developed with predictive functionality for chronic disease management. This platform expansion initiative required close collaboration with medical and technical experts, to deliver impactful, health-enhancing infrastructure.
SaaS | B2B, B2C | HS, HIT, HRC, HCS, AIA | ERP, CRM, SCM, CMS Served as a principal technical advisor and architectural lead for AI startups within the Google Vertex AI Startup Ecosystem. Focused on delivering enterprise-grade AI solutions across HealthTech, MarTech, and HRTech domains. Oversaw AI architecture design, data pipeline strategy, and end-to-end model lifecycle across use cases in NLP, predictive analytics, and behavior modeling. Directed the integration of Google Cloud AI services, TensorFlow, Vertex AI, and BigQuery to accelerate time to production for generative and supervised ML use cases. Reduced average time-to-integration for startup AI pilots from 13 to 6 months. Achievements: • Led architecture design for Calm, Kensho, and Optymyze AI systems • DAU/MAU activation rate increased from 0.2 → 0.5 across 8 startups • Customer effort score reduced from 4.2 → 2.8 (1–5 scale) • Served as AI product mentor for Justworks, Muse, and DataVisor Key Tech Stack: TensorFlow, Vertex AI, Kubeflow Pipelines, BigQuery, AutoML, Kubernetes, Dialogflow, Google Ads API, GA360, Looker, OAuth 2.0, GCP IAM Co-Founder CTO Disney’s MagicBand inspired Patient Tracker, an AI-powered wearable RFID solution to streamline hospital operations. The platform enhanced care coordination, asset tracking, and patient safety, integrating seamlessly with hospital systems.
Led startup-focused residency initiatives across Google’s AI Startup Ecosystems. Developed immersive programs that combined mentorship, workspace access, cloud compute credits, and direct GTM support. Coached founders on Lean Product Management, PLG strategy, and JTBD. Delivered Continuous Discovery workshops and coordinated Design Sprints to refine MMFs. Drove the creation of North Star Metrics to align teams on growth levers and product-market fit. Achievements: • Net revenue retention across cohort increased from 110% → 140% • 3-month residency satisfaction rating: 4.9/5 average • Enhanced VoC process → improved MMF success rate by 60%
Joined Google as an ecosystem consultant supporting G4E. Played a foundational role in building strategic programming for early-stage AI startups. Ran hackathons and curated Design Thinking labs for MVP validation and BDD. Supported portfolio teams in achieving enterprise readiness through data strategy alignment and rapid AI prototyping. Achievements: • Co-led Google Cloud onboarding for early adopters in 5 verticals • Launched 12-month commercialization accelerator in partnership with X • Early-stage partners included Outlier.ai and Kenshoo