Prioritize pain points
Assess AI readiness
Design AI business plans
Set up AI stack
Train test models
Validate value creation
Validate ROI goals
Enable team
Set up AI Ops
AI - Strategy - Product - AgTech - Fintech
Founder at Ceres Imaging
$60MM raised from top-tier VCs
AI - Software - HealthTech - InsureTech
Co-Founder at Health IQ
$0 -> $140MM Annual Rev
AI - Strategy - EdTech - Finance
Former A. Partner at BCG
20 years in transformations
Imagery-based analytics product for farms
AgTech company needs a solution to understand farm health (plant disease, etc.) based on aerial imagery of farms
Designed and build drone-mounted imaging sensors
Built AI models to translate images into plant health data
Advisory to farmers & insights for corrective actions
100s of farmers signed up globally
$10M annual reccuring revenue business
5-10X ROI through improved yields, labor, and costs
Credit risk assessment for farm lender
Major agricultural lender looks to improve credit assessment for farms: underwriting, portfolio monitoring, and risk management
Set up multi-modal data pipeline (loans, satellite & field imagery)
Designed methodology to assess risk events across multiple crops types and regions
Built team of data scientists, product management & customer success for rollout
20% savings in labor efficiency (customer inspections, borrower engagement)
Up to $5M of avoided loan losses through risk alerts and early warning
$1M annual recurrent revenue for the product with just one lender
Personalization of health care plans for patients
Insurance broker needs ways to help millions of seniors navigate find the right plan based on their health records
Prepared dataset of millions of records and health outcomes with 140K+ data points
Trained 600 neural networks (Keras / Tensorflow) to predict disease & recommend plan & benefits
Set up a multidisciplinary team of 10 to build and roll out the product
Customer churn rate reduced by 45%
Onboarded entire sales agent workforce
Alternative admissions process
University removed test scores as decision driver for admissions and needs a more accurate metric to better predict student success once in the program
Assembled data pipeline (e.g. high school performance, essays & interview inputs)
Built regression model with high prediction accuracy and handling of outliers
Set up data governance for ongoing data collection, cleaning, and integration
Freshman attrition rate reduced from above 30% to around 10% within 2 years
Improved diversity of student body (e.g. top grades, clear communicators, strong collaborators)