Zukhriddin Nuriddinov earned his university degree abroad and spent several years living in Singapore. In 2019, he moved back to Tashkent and founded Algorithm Gateway, a custom software development company. One of the team’s projects was a solution for a textile factory that helped uncover hidden losses and cut out production delays. Over the next few years, that MVP grew into a full product: AURA OS, an Industrial AI Operating System for enterprise operations. Today, more than 80 manufacturing companies are active paying customers of AURA OS, and the company is expanding beyond Central Asia.
For the joint Digital Business and Astana Hub project, «100 Startup Stories from Central Eurasia», Zukhriddin told us who the company’s first clients were, why some employees were slowing down the rollout of the system, and how many millions of dollars he has invested in building the product. We also talked about how AURA OS differs from traditional ERP systems and why a profitable business decided it still needed outside investment.
«Production output roughly double after rebalancin»
– Zukhriddin, what were you doing before you launched the startup?
– I got my business degree from Cardiff Metropolitan University in Malaysia, and after graduating, I moved to Singapore. In 2018, I started a fintech company there with my British business partner, James Anderson. We built different solutions for banks and asset management firms, and also worked with blockchain technology across Southeast Asia and Hong Kong.
– How did you come up with the idea for AURA OS?
– In 2019, I moved back to Tashkent for family reasons and hired local developers to help me run the Singapore business remotely. I also started Algorithm Gateway, a custom software development company.
I didn’t want to build a product first and then go looking for customers. I did it the other way around. I thought of people I knew who ran textile manufacturing businesses in different regions and were always complaining about the problems they faced. So I went to one of their factories and asked what exactly wasn’t working for them.
It turned out that factories often run short of raw materials and then have to wait about a month for new supplies to arrive from China or other countries. That can easily push an order past its deadline. If the delay is too long, the customer may ask for a discount, agree to take the goods the following season, or pull out of the deal altogether.
As a result, warehouses end up full of products the factory can’t sell, or has to offload at a steep discount. Margins shrink, while losses keep growing. We wanted to create a system that could anticipate the risk of such failures – such as shortages of raw materials – and suggest what to do before the problem leads to delays and financial losses. That’s how AURA OS came about.
– What exactly were you able to fix with the system?
– AURA OS helped business owners see where they were losing money without even realizing it. At factories and plants in Uzbekistan, there are a lot of hidden costs that managers and owners often don’t notice at all: underused production capacity, slow inventory, unnecessary purchasing, delayed orders, poor workload distribution and working capital trapped inside operations. We started by centralizing all the data on production, sales, inventory, finances, and supply chains. Then the system used AI to analyze where the bottlenecks were and which stages were causing losses.
It also helped factory owners increase production capacity without hiring more people or buying new equipment. Take a textile factory, for example. Workers sit in a row, each handling a different stage of the same production line. Say the person at the first station can process 100 units an hour, the second can only handle 50, and the third can do 100 again. Even though the first and third workers are more efficient, the whole line still moves at just 50 units an hour.
AURA OS made it clear which stage was slowing the whole line down by comparing employee performance with the line’s overall output. That let the factory redistribute people more effectively and place the faster workers at the same stage. In selected cases, we have seen production output roughly double after rebalancing.
We have also worked with manufacturers where management was considering a major new facility and significant hiring to fulfil an international order. In one Uzbekistan textile case, the company had planned approximately $7 million of new facility investment. After analyzing and rebalancing existing production capacity, the business was able to meet its immediate needs without proceeding with that expansion at that stage, while also reducing the additional hiring planned.
The same principle applies to inventory, purchasing, receivables and cash. If a seasonal order is late, finished goods can remain in the warehouse and eventually have to be discounted. If a customer has not paid, the company can struggle to buy raw materials or pay for the next production cycle.
– You describe AURA OS as a system of action. What does that mean?
– Traditional ERP platforms provide the systems of record that businesses rely on. The challenge we focus on is connecting operational information to decisions while there is still time to prevent delays and financial losses.
AURA OS connects to the company’s accounting, warehouse, sales, and other internal data sources, giving it access to information on production, inventory, purchasing, finances, and orders. Its AI intelligence helps teams interpret operational data, identify potential issues and make better-informed decisions.
For example, the aim is to help teams spot a potential raw-material shortage early, understand its impact on production and decide whether to purchase more materials or reallocate existing stock.
AURA OS combines an integrated ERP foundation with AI-native operational intelligence within the same platform. The goal isn't simply to give management another dashboard. It is to connect the information with an action that can change the outcome while there is still time.
«Across my businesses, I’ve worked with more than 500 clients»
– Your first clients were business owners you already knew. How did you find new customers after that?
– Referrals worked really well for us. Textile factories are part of a much larger ecosystem, working with raw material suppliers, manufacturers, distributors, and retail stores.
Once AURA OS was up and running, other companies in the chain noticed that the factory was no longer dealing with the same delays. They started asking about the platform, adopting it at their own businesses, and recommending it to their partners.
For the first few years, we delivered customised software projects for different types of businesses. For example, I also own a network of medical diagnostic centers, and we built a management system for that business too. We developed CRM and HR systems, along with other solutions, and in 2023 we announced AURA OS as a standalone product.
Our focus now is not simply to find more companies. It's to identify manufacturers where operational complexity creates a significant financial opportunity and where AURA OS can deliver measurable value.
– How many clients do you have now?
– More than 80 manufacturing companies are active paying customers of AURA OS today. Across all my businesses, I have worked with more than 500 clients over the years.
The important distinction for us is that AURA OS is now focused much more clearly on manufacturing and enterprise operations.
Our core customers are mid-market and enterprise manufacturers where operational complexity, inventory, production planning and working capital have a material financial impact.
We're particularly focused on sectors such as textile and garment, food and beverage, furniture, packaging and other multi-stage manufacturing businesses.
– What challenges did you face early on?
– At first, many frontline employees weren’t ready to use the new system. Some weren’t very tech-savvy and found it easier to keep records on paper. We soon realized that you can't force people to use the product. The key is to make the system as simple and intuitive as possible, which makes adoption easier.
For example, we added RFID tags to products (they allow items to be identified automatically and information about them to be sent to the system — Digital Business) and installed RFID readers at the warehouse entrance. When a product passes through the scanning zone, the reader automatically detects the tag and sends the data to the system. Employees don’t have to enter anything manually.
There were also cases where some employees deliberately slowed down the rollout of AURA OS. For example, they would ask us to add extra features and refuse to use the product without them. Later, we realized that greater transparency changed established workflows, incentives and accountability within the business, so the transition wasn’t comfortable for everyone.
We’ve learned that successful implementation isn't only about technology. Employees need to understand why the system is good for them too. When the company reduces operational losses and improves cash flow, employees can benefit from greater stability, more predictable salary payments and, where appropriate, the opportunity to participate in the value they help create. That’s why we see AURA OS not simply as a monitoring tool, but as a system that can align the whole organization.
«Around $1.7 million has gone into developing AURA OS»
– How much does it cost to implement AURA OS at a company?
– Pricing depends on the size of the company, the number of users, the scope of deployment and the operational processes being digitized. Our revenue model combines customer deployments with recurring fees for the recently introduced AI intelligence capabilities.
The important point for us is that the core AURA OS platform is standardized and scalable. We configure it around each company's operational environment, but we're not building a separate software product from scratch for every customer.
– How did you fund the project?
– Around $1.7 million has been spent on developing AURA OS over the full history of the project. About 30% came from my personal funds, with the remaining approximately 70% funded by business-generated income reinvested in development, including profits not withdrawn as dividends. Until recently, I didn’t think we needed funding from investors or venture funds. But taking part in the Silkway Accelerator by Astana Hub and Google for Startups changed my mind.
– Why?
– We want to fund the next stage of growth. We are raising $3 million to support further product development, international expansion and commercial growth, as well as the working capital needed to deliver on that growth. I also want to strengthen the organisation so it can operate with less dependence on me personally.
– Which countries are you looking at?
– We’re focusing on the UK, Southeast Asia, Turkey and selected emerging manufacturing markets. We’ve signed LOIs with several companies in the UK and Indonesia, covering contracts worth around $500,000; these remain soft commitments rather than signed customer contracts.
– You were also selected for the AlchemistX & Silicon Valley Residence program by Astana Hub and Silkroad Innovation Hub in Silicon Valley. Is AURA OS entering the US market as well?
– Enterprise sales in the US require more than translating a product into another language. We need to understand local procurement processes, decision-making structures, enterprise security expectations and how large industrial customers evaluate and purchase software.
The Alchemist program gives us an opportunity to build on that experience specifically for the US market. Our international activity in the UK and Southeast Asia has already given us early commercial engagement, and the US is the next major market where we want to build that presence.
– What are your plans for AURA OS over the next few years?
–The goal is to make AURA OS a global AI operating system for enterprise operations, starting with manufacturing. We want to expand the platform across the operational chain: procurement, raw materials, production, inventory, sales, finance, working capital and management action.
We will focus on expanding internationally, increasing the number of enterprise customers, strengthening the AI capabilities of the platform and building a scalable commercial and implementation model.
The journey started with one textile factory in Uzbekistan. The ambition now is to take the same operational intelligence approach to manufacturers globally. Central Asia has a rich history. Great people lived here, and for centuries the region stood at the crossroads of trade and culture. I want to see Central Asia reclaim that role in a new, technological era.