I help digital health, medtech, and SaaS teams integrate LLMs, refine deep learning models, and get AI-powered products ready to ship.
A technology consultancy needed its healthcare and enterprise success stories in front of the right decision-makers, without slow, expensive campaigns.
An LLM-driven outreach engine matched each story to third-party audience data, then sourced, enriched, and personalized every sequence.
100+ engaged leads per client, $2M+ in pipeline, and $188k closed-won in 12 months
A seed-stage AI startup serving the mobile industry needed production-ready marketing assets generated inside its SaaS platform.
I designed and integrated an image-to-image ML pipeline into the product, and built the ICP, pricing, and launch plan around it.
A larger global addressable market, and Phase 1 and 2 launches accelerated by two months
Medical imaging AI research is compute-hungry, and few teams know how much training a result actually needs.
Using 2D nnU-Net, I established efficiency baselines for training and inference. Paper forthcoming
Clear cost baselines that help research teams reach comparable results with less data and compute
A SaaS publishing platform needed AI features that made its customers faster without hurting editorial quality.
I integrated LLMs into the platform's core publishing workflow, with human review built in.
AI features that became a driver of platform growth
Rowan built an automation that connects our Salesforce data to our content marketing system. What would have cost $1,700/month in Zapier fees now runs for under $150/month.
When I spoke with Rowan on the CRM replatforming project, he asked questions that continue to make me think about the direction of the product.
Engagements are typically $5k–$15k.
LLM features for products and automations
Custom models for problems cloud APIs can't solve
Decide what to build, how to frame it and ship it
Remap is my one-person practice. I've spent 20+ years on product, CRM, and integration work for organizations like Banner Health, CHLA, Stanford, the Smithsonian, HP, and many startups in the machine learning space.
I've recently worked in LLM-based marketing automation and now focus on applied AI for digital health and medtech, including LLM integration, evals, product positioning, strategy, and GTM.
Portland, OR
Mostly early-stage digital health, medtech, and SaaS teams. Usually a founder, CTO, or head of product who needs AI integrated.
Inside whatever controls you have and according to strict security and privacy methods. I avoid insecure consumer cloud platforms.
Integrating LLM inference into automations and products, evals design, prompting/context strategy, custom training and fine-tuning of niche DL models; I work with open source/weights models.
Many clients start with a two-week, fixed-price evaluation sprint on one goal but engagements can extend to many months.
Yes, I'm particular about documentation, recorded walkthrough, live trainings, etc, and easy to get ahold of.