While the region spends $386 billion on construction and manufacturing grows at 5.8% annually, its engineers lose a third of their working day to routine. Not on innovation. Not on solving hard problems. On building base 3D models – by hand, for hours, over and over, every single day.
This is not a marginal inefficiency. This is a structural drain on one of the world’s most ambitious industrial programmes. And for years, nobody fixed it.
Danil Rashchupkin spent seven years on the inside of this problem. As founder of Teleport3D, he supplied precision industrial components to some of the region’s largest operators – Tengizchevroil (TCO), Kazakhstan Temir Zholy (KTZ), and major mining enterprises. His engineers were skilled. His clients were demanding. And every new project began the same way: hours lost before a single part could be manufactured.
The bottleneck was always the same. Before anything can be built, machined, or cast, a 3D model must exist. And creating that model – even a basic working version – required a trained CAD engineer, specialised software, and anywhere from two to four hours of focused manual work. Per part. Per revision. Per request.
Across 28 million CAD users worldwide, that adds up to 17 billion hours lost every year. In the Middle East alone, where construction investment hit $386 billion in 2024 and technology spending reached $183 billion, the cost of this inefficiency runs into billions of dollars annually. Research confirms it: traditional spare parts supply chains carry lead times of one to four months. Import markups inflate component costs by three to five times. Up to 40% of enterprise capital can be frozen in warehouse inventory waiting for the right part.
One production stoppage at a major facility can cost more than an entire month of engineering salaries. And the first bottleneck – always – is the model.
Rashchupkin searched for a solution. He evaluated every tool on the market. Generic AI generators produced visually impressive shapes that fell apart under engineering scrutiny. CAD platforms required deep expertise and hours of setup before a usable output appeared. Nothing sat in the middle — fast enough for production pressure, precise enough for real engineering work.
So he built it himself.
Nika AI is an artificial intelligence assistant designed specifically for engineers and technical specialists. It does one thing better than anything else on the market: it takes a photograph, a hand-drawn sketch, or a plain-language description, and returns a working base 3D model in five minutes.
Not a render. Not a concept illustration. A base model – structurally coherent, ready to open in CAD software, ready for the engineer to refine and send to production.
The numbers that follow are not projections. They are the documented impact of applying AI-driven digital manufacturing to real industrial workflows: procurement cycle times reduced by up to 90%. Losses from equipment downtime cut by up to 40%. Design and repair costs optimised across the board. For a region where a single production stoppage at an oil facility, a rail depot, or a mining operation can cost millions of dollars per hour, these are not incremental improvements. They are competitive transformations.
The first version of Nika AI was honest about its limits. It generated shapes. It answered technical questions. But it was not yet the tool an engineer would trust when production pressure was real. The outputs looked promising – not yet reliable enough to stake a project on.
The team kept iterating. Four people: a founder with seven years of industrial client experience, a CTO with expertise in high-load backend systems and LLM architecture, a 3D technologies specialist with WorldSkills Kazakhstan credentials, and a marketing and AI product lead. They tested on real orders, not controlled demos. They spoke to engineers who would lose money if the tool failed them. They rebuilt until the output was something a practitioner would trust without hesitation.
The breakthrough was focus. They stopped trying to build a universal 3D generator. They committed to solving one specific, expensive, daily problem for one specific professional – the engineer who needs a working base model, fast, to start from. Everything else became secondary.
Today, Nika AI serves engineers in 96 countries. More than 73,000 technical consultations have been delivered through the platform. Over 190,000 3D models have been downloaded. Monthly user growth consistently exceeds 1,500 new engineers. Revenue is live. The project is backed by Terrikon Valley fund and three angel investors.
The Middle East is not just a market for Nika AI. It is the natural home of its next chapter.
Vision 2030 in Saudi Arabia, the UAE Centennial 2071, Qatar’s National Vision – these are not policy documents. They are industrial transformation programmes at a scale the world has rarely seen. Engineering firm revenues in the region grew 30.4% in 2024, the strongest performance since 2018. Technology investment is projected to reach $24.7 billion by 2030. The demand for tools that make engineers faster, more productive, and less dependent on manual process has never been greater.
Nika AI addresses that demand at its most fundamental level – the moment before production begins, when a model must be created and every hour of delay has a price.
The team is ready for a new investment round to advance the AI model, expand platform capabilities, and build the partnerships that bring Nika AI to the engineers reshaping this region.
Strategic partners who understand industrial workflows, engineering productivity, and the scale of what is being built across the Gulf will find in Nika AI a technology already proven in the field, already trusted by engineers in 96 countries, and already generating revenue at pre-seed stage.
The lost hours of the Middle East’s engineers are not inevitable. They are a problem with a solution. And the solution is already running.
Danil Rashchupkin is a practicing engineer and the founder of Teleport3D and Nika AI. With years of industrial experience, he developed solutions that address key challenges for engineers in the industry
