Selected work

Products that shipped and solved operating problems.

A focused sample of production client work across AI vision, healthcare data platforms, and operational forecasting.

ClaimTally AI
InsurTech · AI vision

ClaimTally AI

ClaimTally AI generates structured home inventories for insurance-loss claims from photos and video. It then uses an AI-enabled shopping workflow to find close matches for lost items and estimate current replacement cost.

The product combines computer vision, language models, and web workflows in one insurance claim process.

Core workAI vision, product engineering, replacement-cost workflow
Selected stackPython, Django, AWS EKS, Tailwind, HTMX, GPT-4o, Claude

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The Alinea Group
Healthcare · Data platform

Alinea

A healthcare data-platform build required a credible delivery path after the original offshore approach failed to produce the needed result. SaaS Factory stepped in with the product and engineering capacity to move the platform forward.

The work centered on a production 340B platform and the data architecture, application layer, analytics, and infrastructure required to support it.

Core workPlatform recovery, data engineering, full-stack delivery
Selected stackPython, Django, React, AWS EKS, Redshift, Pandas, GPT-4o

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TimeDoc Health
Healthcare · Operations data science

TimeDoc

Managing care for tens of thousands of Medicare patients creates a demanding workforce-planning problem. SaaS Factory built operational models and analysis tools that predicted productivity within 1% of actual and forecasted needs up to six months ahead on a rolling basis.

The result gave operating leaders a more reliable way to anticipate capacity and make resource decisions before constraints became urgent.

Measured outcomeProductivity prediction within 1% of actual
Selected stackPython, Pandas, Google BigQuery, statistics

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How to read the portfolio

Each project turns difficult operating inputs into a production system.

01

Messy inputs become useful systems

Photos, videos, healthcare records, operational data, and human workflows become structured products people can act on.

02

AI serves the product

Models are selected around the user’s job, data, controls, and acceptable failure modes.

03

Delivery has to survive production

Architecture, cloud operations, data quality, usability, and business ownership matter as much as the demo.

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We are most useful when the work requires product judgment, technical depth, and direct ownership.

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