Rehinged began as a venture-backed data science company in 2018. We spent years building market infrastructure, healthcare intelligence and commercial models. As AI systems became capable enough to work across that foundation, work that once required specialist teams and weeks could be drafted in minutes, refined with the client, and carried forward inside a persistent intelligence system.
Rehinged was formed to analyze markets, evaluate technology opportunities and help growth-stage companies turn data into commercial decisions — investing early in data ingestion, cleaning and normalization, analytics, market modeling, and early AI and NLP.
The limitation was not imagination. It was economics and reliability: expensive specialists, cumbersome workflows, slow production, and models not yet good enough for many commercial use cases.
Good enough to sit inside a broader system. The underlying need had existed for years — the economics changed.
Rehinged licensed its scoring technology to partners while customer revenue funded the next generation of its healthcare infrastructure — restructuring data, models and workflows so they could be used by increasingly capable AI systems.
Rehinged rebuilt its infrastructure around specialized agents, parallel research, tools and paid sources, memory, standing methodologies, client-specific context, and persistent application delivery. Work that once took weeks and large specialist teams can now be drafted in minutes and refined with the client.
A structured healthcare intelligence foundation, adaptive client-specific models, agent-driven research and enrichment, persistent memory, a working client application, and finished commercial work.
Rehinged has spent years structuring healthcare provider and prescriber markets. Healthcare combines:
with fragmented commercial markets underneath it.
with genuinely difficult targeting.
and buyers who need intelligence before they can act.
Healthcare is where Rehinged’s existing intelligence layer and proprietary commercial models are deepest. It gives clients the greatest immediate advantage — but it is the starting point, not the boundary of the markets the system can build.
Facility and prescriber intelligence, ICP models and scoring delivered through a defined healthcare interface built on the same underlying data foundation.
Adaptive client-specific models, agents, enrichment, memory, persistent workspaces and finished commercial work built around the client’s market and objectives.
Rehinged is a small core team working with agents we built ourselves, on a foundation laid by more than thirty people since 2018. We’re an AI-forward company, and that means something specific.
Our agents analyze large sets of market data. They write and review the code in our product. They build and improve other agents. They design product, run a hostile QA on client output before a person reviews it, create engineering handoffs and Jira tickets, built this website, use our own product to find and introduce us to the companies we’d like to work with, support leadership on strategy, handle administrative work, and recommend what to improve next.
People decide what to focus on, review what comes back, and either accept the work or send it back until it’s right. That loop is the company. When an engagement needs more engineers, we add them to the engagement; the loop doesn’t change.
For years, the intelligence companies needed was technically possible but economically impractical to produce.
AI changed the production economics. Rehinged had already spent years building the data infrastructure, market models and commercial methodology needed to take advantage of that change.
The finished work is readable in full — and your own market is a free Market Draft away.
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