Aulius is the embedded AI strategy and execution partner for Asia's growth and cross-border companies.
Strategy, build, deployment and continuous improvement — carried by one team, from the first question to the system that runs every day.
AI has advanced far enough to create real value for almost every business — lower operating cost, faster and better decisions, capacity no longer bound by headcount, new products and new revenue.
Most companies are still at the beginning. The board feels the pressure. Underneath, the data is fragmented, the workflows are legacy, and there is no one inside the building who can bridge the two.
AI capability is no longer the only bottleneck. Enterprise judgment and execution are.
The hardest part of enterprise AI happens before the first line of code is written.
We are neither an advisory firm nor a staffing shop. We take the business problem from opportunity identification through to production and ongoing operation. We work with internal IT, not around it.
Others start with what AI can do. Aulius starts with what the business needs to achieve.
Enterprise AI cannot be built on the assumption that the model is always right. Every system we build separates three kinds of work, and holds the boundary between them.
Unstructured documents, ambiguous language, context, classification and mapping — the work fixed rules cannot cover.
Arithmetic, reconciliation, formats, fixed business rules, data relationships — the work that must be exactly right.
Low-confidence results, mismatches, exceptions, approvals, negotiation — and final accountability.
AI for ambiguity. Code for certainty. Humans for judgment.
Probabilistic intelligence inside deterministic boundaries.
The goal is not to remove people from the loop. It is to make every minute of human attention count.
Clients are not named and engagement detail is withheld by default. Confidentiality is part of what we sell.
A knowledge-work business whose growth was capped by the volume of documents its people had to handle by hand. We rebuilt the core operation around AI-native processing — with the output landing in the formats their staff already knew, so nothing had to be relearned.
We then built the operating platform for the business line that ceiling had been blocking.
We did not start by building AI. We started by establishing what the company's data could honestly support, and unified it into a single definition of the business. If the layer underneath is not true, nothing built on top of it is either.
One shared set of numbers, and analysis, planning and costing standing on top of it.
An operation running out of shared mailboxes, where every change of instruction had to be caught, reconciled and recorded by a person. We designed the workflow that reads what arrives, keeps every version accounted for, and prepares the paperwork.
Every commitment made to a counterparty stays with a human being.
A domain the founding team knows from the inside. The system follows an institutional process end to end, and reconciles each new document against everything already known rather than reading it in isolation.
Institutional memory that compounds inside the institution, instead of leaving with the person who built it.
We do not serve everyone. We work with companies that have a real business underneath, understand what good execution is worth, and are prepared to pay for judgment as well as delivery.
Our capabilities are horizontal. Our go-to-market is focused.
Each engagement is scoped by module. You get value from the first one, and we keep finding the next from inside your operation.
Design, development, integration, deployment and acceptance of a defined module.
After acceptance: running, maintaining and improving it as usage, models and cost move.
On live engagements, small issues and workflow adjustments are typically resolved the same day or the next. The feedback loop is part of the product, not post-project maintenance.
Our founding team comes from the investment, strategy and technology divisions of J.P. Morgan, Standard Chartered and other leading global financial institutions, and from the front rank of financial technology — with deep experience taking enterprise AI all the way into production. More than a decade working together.
The founders are hands-on in the product direction and AI architecture of every engagement — the people who assess the opportunity are the people who design and ship the system.
Aulius is headquartered in Hong Kong and works across the Greater Bay Area, the Yangtze River Delta and, increasingly, other markets in Asia-Pacific.
Institutional judgment. Startup speed. AI-native execution.
We will tell you honestly whether AI can fix it today — and if it can, where to start. No pitch deck required.
Clients bring us operational pain — not technical specifications.