Four AI Tools Built to Take the Grind Out of Operations

AI is easy to demonstrate. Operationalising it is harder.

In day-to-day operations, information rarely arrives neatly. Data sits across emails, PDFs and spreadsheets. Exceptions require judgment. Transactions keep moving. And mistakes have real consequences.

At Li & Fung’s AI Excitement Day in Hong Kong on 2 September 2026, Neo Tangent demonstrated four AI-enabled solutions designed for exactly this environment. Over 300 attendees visited the Neo Tangent booth to see how AI is already being applied to real operational work: from order creation and document validation to trade classification and finance posting.

What held their attention was not simply what the technology could do, but the practical problems it was built to solve.

It Starts With the Data That Doesn’t Arrive Neatly

Every operation depends on information, but that information often arrives in different formats and through different channels: customer emails, PDFs, spreadsheets, forms and supporting documents.

OrbitFLOW helps turn that unstructured information into structured, system-ready data. It extracts relevant information, applies business rules and supports downstream workflows, reducing the need for operators to repeatedly read, interpret and re-key the same information.

The aim is not automation for its own sake. It is to remove repetitive work from the process, while keeping people involved where review, judgment and exceptions matter.

Watch the OrbitFLOW demo →

Then Come the Decisions That Carry Risk

Some operational decisions have greater consequences than others.

A product classified under the wrong customs code, or a discrepancy missed in a shipping document, can lead to delays, additional cost or compliance risk.

OrbitDUTY supports product classification and duty research across multiple markets, helping teams work through HS/HTS classifications and relevant tariff information more efficiently.

OrbitMATCH, meanwhile, compares shipping documents against source information and business rules to identify discrepancies, missing information and potential exceptions.

In both cases, the principle is the same: let technology handle the routine comparison and research, so people can focus their attention on the exceptions and decisions that genuinely require expertise.

Watch the OrbitDUTY demo →
Watch the OrbitMATCH demo →

And the Transactions That Never Stop

Finance operations face a different challenge: volume.

Invoices arrive continuously, and every transaction needs to be processed accurately, reviewed appropriately and posted into the financial system.

OrbitPOST uses AI-assisted extraction and recommendation to help operators process invoices more efficiently. Relevant source information is highlighted for review, posting values are recommended, and operators remain responsible for validation and approval before submission.

It is a practical example of how AI can reduce repetitive handling without removing the control and accountability that finance operations require.

Watch the OrbitPOST demo →

How Neo Tangent Can Help

The technology is only the visible part.

What makes these solutions work in a live operation is the understanding around them: knowing which steps should be automated, which business rules need to be applied, where exceptions are likely to occur and where human judgment must remain.

Neo Tangent combines operational expertise with process redesign, workflow automation and AI to improve the way work gets done.

The objective is not simply to introduce another technology tool. It is to redesign operational processes so they can become more efficient, more consistent and more scalable.

The Real Question

For operations leaders, the question around AI is increasingly moving beyond what it can do in a demonstration.

The more important question is whether it can perform reliably as part of the operation: across repetitive work, real transactions and real exceptions, day after day.

That is where AI starts to create meaningful business value: not as something running alongside the operation, but as part of how the operation itself works.