South Korea’s Industrial AI Startups Grow Sales as Factory Deployments Expand

South Korean AI startups focused on manufacturing and other industry-specific applications are recording stronger sales as companies move AI into real operating environments, although profitability remains a challenge for much of the sector.

Second-quarter results from several KOSDAQ-listed AI companies showed that businesses securing projects in manufacturing, defence, healthcare and the public sector were generally able to increase revenue faster than companies still focused on general-purpose AI services or early-stage products.

The results highlight a growing divide in South Korea’s AI market as customers place greater emphasis on technologies that can demonstrate measurable productivity gains and solve specific operational problems.

MakinaRocks Expands Industrial AI Deployments

Physical AI company MakinaRocks reported second-quarter sales of 4 billion won, an increase of 168.6% from a year earlier.

Its operating loss narrowed 33.4% to 1.8 billion won.

Growth was supported by expanding manufacturing projects, including the broader deployment of predictive maintenance AI across around 1,400 industrial robots at Hyundai Motor’s global production facilities.

The company has also expanded beyond manufacturing after securing a project with South Korea’s Agency for Defense Development to build a development environment for an AI staff agent.

The results show how AI applications tied directly to industrial equipment and operational requirements are beginning to generate commercial demand.

Manufacturing-Specific AI Gains Momentum

Konan Technology also recorded stronger performance, with second-quarter sales increasing 23.1% year on year to 4.17 billion won.

Its operating loss narrowed 36.6% to approximately 2.82 billion won.

The company has been expanding from public-sector AI projects into manufacturing, defence and legal applications.

Together with Naver Cloud, Konan Technology is developing manufacturing- and defence-specific large language models and physical AI technologies.

The expansion reflects growing demand for AI systems designed around specific industries rather than general-purpose applications.

Healthcare AI Also Records Growth

Healthcare-focused applications provided another area of stronger performance.

SELVAS AI reported consolidated second-quarter sales of 33.34 billion won, up 19.1% from the previous year.

Operating profit reached 1.78 billion won, around 24.6 times higher year on year, supported by improved results from medical-device affiliates including Mediana.

SELVAS AI is expanding an AI medical platform that integrates patient monitoring systems with central monitoring platforms and electronic medical records.

However, its standalone AI business remained weaker, showing that commercial performance can vary significantly between applications even within the same company.

General-Purpose AI Companies Face Profitability Pressure

Other AI companies have found it more difficult to translate new AI agent businesses into stronger financial results.

ESTsoft recorded a 4.7% decline in second-quarter sales and moved into an operating loss.

WISEnut’s revenue fell 8.7%, while Saltlux increased sales by 64.3% but saw its operating loss widen.

All three companies have been expanding AI agent businesses, but these investments have yet to produce stronger profitability.

MAUM.AI also reported weaker results despite investing in physical AI as a future growth area.

Its second-quarter sales fell 58.2% to 962 million won, while its operating loss increased 88% to more than 3 billion won.

AI Investment Costs Remain High

Rapid revenue growth is also not necessarily translating into profits.

Crowdworks increased second-quarter sales 17.9%, but its operating loss widened 19.2%.

AI optimisation company Nota recorded a much stronger increase in revenue, with sales rising around 7.6 times year on year to 3.82 billion won, but its operating loss also increased 59.7% to 6.19 billion won.

The companies are expanding across AI data, physical AI and model optimisation, but continued investment in technology and product development is weighing on profitability.

Industrial Use Cases Create Clearer Commercial Demand

Industry observers cited by ChosunBiz identified a focus on solving specific operational problems as a common feature among AI companies showing stronger commercial performance.

Applications such as predicting manufacturing equipment failures provide companies with relatively clear opportunities to measure productivity improvements, cost savings and operational benefits.

By comparison, companies developing general-purpose AI platforms or products without an established industry use case may face longer timelines before investment translates into recurring sales.

The shift suggests that the South Korean AI sector is moving beyond a stage where technological capability alone determines competitiveness.

Industrial AI Moves From Technology to Execution

South Korea’s latest AI company results highlight a broader transition taking place across the sector.

AI companies are increasingly being evaluated on whether their technologies can operate successfully in real industrial environments and generate repeat business.

Manufacturing is emerging as one of the clearest areas for this transition, particularly through predictive maintenance, physical AI and industry-specific models.

As industrial adoption expands, AI providers capable of connecting technology with measurable improvements in productivity and equipment performance are increasingly separating themselves from companies still focused primarily on experimentation and product development.