Operations & Scale

TECO Acquires Malaysian Engineering Firm to Expand Modular AI Data Center Business

The US$50.8 million deal strengthens TECO’s push into modular infrastructure and faster data center deployment across Southeast Asia.

Updated

May 26, 2026 5:39 PM

Kuala Lumpur, Malaysia. PHOTO: UNSPLASH

TECO Electric & Machinery is expanding further into Southeast Asia’s AI data center infrastructure market through a new acquisition in Malaysia.

The Taiwan-based company has signed an agreement to acquire approximately 78 percent of Malaysian engineering firm Dynaciate Engineering in a deal valued at around MYR 200 million (US$50.8 million). According to TECO, the acquisition is aimed at strengthening its modular data center manufacturing capabilities and supporting its expansion across Southeast Asia’s data center infrastructure sector.

Under the agreement, Dynaciate will become TECO’s global manufacturing hub for modular data center and power equipment products. The company will also serve as an engineering hub supporting TECO’s regional expansion efforts, particularly in AI data center infrastructure projects.

TECO Chairman Morris Li said the integration between both companies has improved execution efficiency and increased the company’s in-house modular prefabrication capabilities. According to the company, the collaboration has reduced data center delivery timelines to as little as six months.

Dynaciate is headquartered in Johor Bahru, Malaysia. Its facilities span approximately 36,000 square meters and include eight production buildings focused on stainless steel and carbon steel fabrication. The company said the site is also eligible for export tax incentives that support future global supply chain deployment.

According to TECO, Dynaciate has experience in engineering, steel fabrication and large-scale industrial projects for multinational corporations. The company added that Dynaciate has expanded into the data center engineering market since 2025 through projects involving international cloud service provider clients.

TECO estimates that after the acquisition, around 65 percent of future data center-related revenue will come from modular data centers and prefabricated products, while the remaining 35 percent will come from AI data center engineering projects. The company also forecasts that data center-related revenue within its Power & Energy Business Group will rise from below 10 percent to 30 percent this year.

Dynaciate CEO Ng Kim Thiea said the company is entering a new phase of growth through the partnership with TECO. He added that Dynaciate has extensive experience supporting engineering and industrial projects across the region.

The acquisition marks a further expansion of TECO’s presence in the AI data center infrastructure sector as companies continue increasing investments in modular infrastructure and regional engineering capacity.

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Artificial Intelligence

DeepCyte Raises US$1.5M to Use AI and Single-Cell Analysis to Predict Drug Toxicity

A new approach examines how individual cells respond to drugs, aiming to identify risks earlier in development.

Updated

May 1, 2026 2:25 PM

Close up of a capsule blister pack. PHOTO: UNSPLASH

DeepCyte, a startup in the drug development space, is focusing on a long-standing problem: why drugs that appear safe in early testing still fail in clinical trials or are withdrawn later due to toxicity. DeepCyte has launched with US$1.5 million in seed funding to build tools that detect and explain the harmful effects of drugs at much earlier stages.

The startup’s approach focuses on how individual cells respond to a drug. Instead of analysing cells in bulk, it studies them one by one. This helps capture differences in how cells react, which are often missed in traditional testing methods.

Drug toxicity remains one of the main reasons for failure in drug development. Methods such as animal testing and bulk cell analysis do not always reflect how human cells behave. This gap has pushed the industry to look for more reliable and human-relevant ways to test drug safety.

DeepCyte combines cell-level data with artificial intelligence. Its platform, MetaCore, studies what is happening inside individual cells by capturing detailed molecular information. This data is used to build large datasets that can train AI models.

Additionally, the company has developed an AI system called DeeImmuno. It is designed to predict whether a drug could be toxic and identify the biological reasons behind it. In internal testing on 100 drugs, the system identified different types of toxicity and their underlying mechanisms with a reported accuracy of 94 percent.

The focus on explaining why a drug is toxic, not just whether it is, reflects a broader shift in the industry. Regulators such as the U.S. Food and Drug Administration and the European Medicines Agency have been encouraging methods that rely more on human cell data and clearer biological evidence. The seed funding will be used to develop and scale these tools. The company aims to help drug developers make earlier decisions, which could reduce costly failures in later stages. Whether tools like this become widely used will depend on how they perform in real-world settings. For now, DeepCyte’s approach highlights a growing effort to make drug testing more precise by focusing on how drugs affect cells at the most detailed level.