Introducing SemantIQ

TL;DR

• Healthcare doesn’t have a data shortage. It has a usability problem.
• SemantIQ is building the intelligence layer for healthcare data, starting with claims and patient journey data.
• You can run SemantIQ in your own cloud, on your own data, with your own rules.
• The platform is built on a healthcare-native semantic layer, agentic workflows, and a context engine purpose-built for claims.

Over the past decade, I’ve been obsessed with a deceptively simple question:

Why does it take so much effort to turn data into decisions - especially in industries where the stakes are highest?

That question really hit me while building PlaceIQ. We were early to a major platform shift: location and geo-based data was exploding in volume, but it was really only usable by highly specialized technical teams.

The breakthrough wasn’t better data; it was making the data easy for non-technical decision makers to use.

The lesson stuck with me: Data needs to be usable, not just accessible. When data lives at the fingertips of decision-makers, they use it more - and make better decisions because of it.

This belief is what led to the creation of SemantIQ.

When we started SemantIQ, we had to pick where to begin. We chose healthcare claims data, because it is simultaneously the most valuable and the most unusable data in healthcare.

Claims data contains the longitudinal truth of how patients move through the healthcare system: diagnoses, therapies, procedures, providers, switches, and outcomes. But it is fragmented, messy, heavily governed, and encoded in ways that make it accessible only to highly specialized teams.

In other words: it’s exactly the kind of data that proves whether you’ve actually solved the usability problem.

Our mission is simple: to help health organizations get useful insights from data faster - so they can make better decisions to act on them and improve patient outcomes.

SemantIQ runs in your own cloud, on your own data, with your own rules. And instead of weeks of back-and-forth between business and data teams, you can get decision-ready answers in minutes. For the first time, that means business users, not just technical specialists, can actually use healthcare data directly.

The “Now What?” Problem:

Over the last decade, organizations have invested billions of dollars in data infrastructure.

The’ve licensed data
They’ve moved it to the cloud.
They’ve invested in clean rooms and modern data platforms.

And yet, a familiar question keeps coming up:

Now what?

Bringing data into one place does not make it understandable or usable.. And it certainly does not make it actionable for the people closest to decisions.

Definitions live in documentation.
Logic lives in notebooks.
Assumptions live in people’s heads, built up over years of exchanging tribal knowledge.
Every new question turns into a custom project or another Jira ticket in a data team's long backlog.

This is the gap SemantIQ closes.

Imagine a brand or commercial analytics leader at a life sciences company asking:

 “Which healthcare providers are treating the most Type 2 diabetes patients, which ones are switching patients to our competitor, which ones are early adopters of new therapies - and how does that differ by geography, specialty, and payer access?”

Today, answering that question requires stitching together claims data, patient journeys, market share reports, access data, and multiple internal dashboards - often taking weeks of analyst time and several rounds of interpretation.

With SemantIQ’s AI-native platform, this becomes a single question in plain English - and behind the scenes, a team of AI agents plans, executes, validates, and explains the entire analysis on top of the semantic layer by:

• Explaining why the numbers look the way they do
• Producing a decision-ready output with full transparency and auditability
• Enabling the user to inspect and change assumptions

Why Now: AI Is Changing the Landscape

We’re at the start of a big shift in how software gets built and how work gets done.

AI is moving from something you “use” to something that actually does work for you - planning, executing, validating, and explaining. As Andrej Karpathy put it, we’re entering a software 3.0 era. 

At the same time, when analysis becomes faster, cheaper, and easier, people don’t use it less - they use it everywhere.

But in healthcare, “almost right” is often just wrong, which means this only works if the system actually understands the domain it’s operating in. It must be governed, audited, and trusted.

This is why the semantic layer matters; not as a reporting feature, but as the foundation for decision-ready AI. It encodes the rules, concepts and business logic into the data itself. 

Without it, agents hallucinate. With it, agents reason.

Why Healthcare: The Cost-Care Disconnect

Healthcare produces more data than almost any industry, yet it still struggles with cost, access, and outcomes. The gap between access and affordability continues to widen.

The stakes are higher. 
The data is more complex. 
The rules are stricter. 
And the tools are harder to use.

This is not a data availability problem. It’s a data usability and data insights problem. And in healthcare, that gap has real consequences.

Promising therapies take years longer to reach the patients who would benefit most; Patients (and caregivers) don’t know which hospitals or doctors actually get better outcomes for their condition; Health systems waste billions on avoidable costs they can’t reliably pinpoint or prevent.

The Bet We’re Making

SemantIQ is building data infrastructure for healthcare - an intelligence layer you can trust, understand, and actually use, inside your own governed environments.

We’re making a few explicit bets:

1. Healthcare claims data requires context-native intelligence, not generic AI
Healthcare data is becoming first-party and fragmented. More and more teams want to control their own data. Context matters. Without healthcare-specific semantics, even the best models produce confident but wrong answers.

2. The semantic layer is the foundation for trustworthy agents
The real advantage won’t come from having the best model or the prettiest UI. It will come from understanding healthcare data, and workflows.

3. Agents will replace dashboards, tickets, and ad-hoc analysis
The future of analytics is agentic workflows that reason, plan, execute, validate, and explain. Human-in-the-loop, machine-orchestrated.

4. Governance, auditability, and explainability are the product
In healthcare, trust is not a checkbox. It is the buying decision.

What We’ve Already Learned Early

We spent time with two of the largest foundations in the country. 

One focused on health policy but felt chronically data deficient. The other had invested heavily in claims data, but ultimately wound down the initiative because the technical and clinical burden to sustain it was too high. 

Everywhere we went, the story was the same: the data existed, the motivation existed - but the tools didn’t.

These organizations weren’t asking for more reports. They were asking for understanding without needing an army of specialists to get there.

Why This Matters

This problem is personal.

Many of us have had family members who needed care. You can find doctors with reviews online. You can find hospitals nearby. But you can’t easily answer questions like:

• Who in this area treats the most patients with this condition?
• Who performs this procedure most often, and with the best outcomes?
• What do infection and complication rates really look like?
• If I switch to the generic, what will it cost me at the pharmacy on my plan?

That information exists. It’s just hard to reach.

Our Vision

Our vision is to make healthcare data useful to anyone who’s trying to make a decision. By building agentic, context-aware systems, SemantIQ aims to:

Level the Playing Field: Make healthcare insights usable to anyone with data, regardless of organizational role or technical resources, from data scientists and analytics teams to business users and operators.

Make Compliance Effortless : Embed privacy, governance, and auditability directly into every AI workflow, so trust, compliance, and oversight are built-in, not bolted on.‍

Advance Health Insights Through Greater Access : Enable a much broader ecosystem of innovation, including emerging life sciences and biopharma teams, universities, nonprofits, foundations, and public-interest organizations, enabling breakthroughs that were previously hidden by cost, complexity, and opaque data structures.

Looking Ahead

Healthcare doesn’t need more dashboards; It needs fewer barriers between questions and decisions.

If AI is truly a democratization force, it must show up where the problems are hardest and the stakes are highest. 

That’s the journey SemantIQ is on. It’s Day 1. 

Our agents are live, and we’re working with early customers and design partners in 2026. If this is something you want to be part of, we’d love to talk.

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