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We sell to people who need precision, consistency, and explainability from AI, because they work in the domains where a nearly right answer is the wrong one.
  • A chief medical officer whose treatment protocol gets audited.
  • A credit head whose decision gets appealed.
  • A project director whose reading of a permit gets litigated.
Their knowledge sits across data systems, standards, and the judgment of a few senior people, and the AI they use has to reason across all of it, not search part of it. Clients are on Clients. Partners are on Partners.

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The buyer, in one view

Where they live

Regulated industries: healthcare, financial services, government, and the project industries that lead each regional economy. Inside them, the domains where the answer is sensitive: value-based care, credit and claims, permits and contracts, safety and submissions. And inside those, the organizations with a named person accountable for the answer.

What they need

Precision, because the domain is sensitive.Consistency, because the question will be asked again and the answers compared.Explainability, because someone will ask how it was reached.

What they do

Their experts sculpt the reasoning. Definitions, rules, and judgment go in once, in their own words, and every answer the enterprise gets inherits them. That is where the confidence comes from: they trust the AI because they shaped how it thinks, and what they sculpt compounds rather than churns.
Read left to right, that is one buyer: an organization in a regulated industry, working in a domain where a nearly right answer is the wrong one, whose experts sculpt how the AI reasons so the enterprise can stand behind every answer. The rest of this page is where that buyer goes deepest, and where they are concentrated.

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Where we focus in healthcare

Value-based care. It is the hardest reasoning problem in the most sensitive domain there is, and it is where an incomplete answer costs the most. We came out of this work, on both sides of the world, and built AiQL because nothing on the market could hold it together. Every episode of care leaves five records behind, each owned by someone different. What should have happened is the clinical guideline, owned by the medical societies. What did happen is the medical record, owned by the provider. What the outcome was is the outcome measure set. What was billed is the claim, submitted by the provider and adjudicated by the payer. What gets paid is the contract, owned by both. Each lives in its own system and its own format, and nobody’s job is to hold all five together. So the questions that matter fall between them.

Care gap detection

Between the guideline and the record. What should have happened, against what did.Are patients being managed in line with our own guidelines for this condition?

Outcome attribution

Between the record and the outcome. What we did, linked to how the patient actually did.Which care patterns produce the best outcomes, and which produce harm?

Outcome-integrity audit

Between the outcome and the claim. What happened clinically, against what we billed.Do our claims reflect what the outcome data shows actually happened?

Value-based compliance

Between the claim and the contract. What we billed, against what the contract pays for.Which episodes earned the value-based payment under our contract?
That is what we sculpt in healthcare: the reasoning that holds all five records together around one patient, so each of those four questions gets a precise, consistent, explainable answer. What the organization gets from it is the operating side of value-based care: outcomes-linked contracts, risk stratification, episode-of-care economics, and risk-adjusted performance, all drawn from the same structure.
The moment a health system starts paying for outcomes instead of volume, it inherits these four questions regardless of country. We have built the reasoning for them once already. Most of it carries.

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The regions, in the order we work them

We sell from where we sit. The parent company is in Singapore, the subsidiaries are in Riyadh and Chicago, and the European Union is served from those three until it earns its own. Outside healthcare we do not chase every industry in every region. Each economy puts its money and its risk into a few sectors, and we go where that concentration already is. Entity details are on Legal. Where data lives is on Data regions.
1

Singapore

Home, and where we start. The parent is here, and this is where we expect our most careful, most compliance-led selling. Singapore’s economy is a handful of deep, heavily supervised sectors, each with dense rules and no tolerance for a plausible wrong answer, which is our buyer exactly. It is also the doorway into Southeast Asia.
  • Healthcare. A public system that has started paying for prevention and outcomes.
  • Financial services. Banks, insurers, and asset managers under MAS supervision.
  • Maritime and trade. The port, and the contracts and classification standards behind it.
  • Pharmaceutical manufacturing. Regulated production and submissions from the regional base.
Data stays in the region.
2

Middle East

This is where we have proof. Every client deployment we can show publicly is in the Middle East, and the Riyadh subsidiary is where the company has sold so far. The region runs on national transformation programs, and those programs are very large, very regulated, and knowledge-intensive. All of them have someone accountable for the answer.
  • Healthcare. The health sector transformation that gave us our first value-based care deployment.
  • Construction and real estate. Giga-projects where contracts, codes, and permits are read at scale.
  • Oil, gas, and energy. Asset, safety, and contract standards, and the energy transition underneath them.
  • Culture and tourism. A sector being built from nothing, with new licensing, heritage rules, and hospitality standards behind it.
Government usually sits behind all four, and government is a client in its own right. Data stays in the region.
3

United States

Where we came from in healthcare. Chicago is the subsidiary, and healthcare is why it is there. The United States is the deepest value-based care market in the world: providers, payers, and state programs all running outcome-based models, each with its own rulebook. We have worked inside a multi-hospital health system, an academic medical center, and a state health marketplace in that city, and those relationships are where the first conversations start.
  • Healthcare, in full depth. Providers, payers, and state programs.
  • The natural neighbors. Pharma and life sciences, where the regulatory work has the same shape, and financial services and insurance, where every credit and claims decision has to be explained to someone.
Data stays in the country.
4

European Union

Last, and we say so. The EU is served remotely, with EU data residency, from the existing entities. It is also the market where regulation is doing the selling for us: the EU’s rules on high-risk AI make traceable, defensible reasoning a legal requirement in healthcare, credit, insurance, and public services, which reads like a description of our product.
  • Healthcare and pharma first. National systems moving to outcome-based models, and EMA oversight over Europe’s manufacturing base.
  • Then financial services. Supervised banks and insurers with auditable decision requirements.
Data stays in the EU.

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What this adds up to

One buyer

Defined by the need for precision, consistency, and explainability, not by industry.

One global sector

Healthcare, taken deep in every region, because the reasoning transfers.

Regional sectors by concentration

A short list per region, chosen by where each economy puts its risk.
The platform does not change between them. The experts sculpting the reasoning do. That is how we can be global in one sector and local in the rest without fragmenting what we build.
Deployment choices are separate from all of this. Large regulated and government buyers tend to sit on dedicated or split tenancy under custom deployments. Smaller private buyers tend to sit on self-service SaaS. See Data regions and Tenancy tiers.