<table name="logo_release" border="0" cellspacing="10" cellpadding="5" align="right"> <tbody> <tr> <td><img src="https://mmx.prnasia.com/media/MS1965012/20260805221901EDT_image_1.jpg?id=OA2829364&amp;p=medium600" border="0" alt="" title="logo" hspace="0" vspace="0" width="118" /></td> </tr> </tbody> </table> Singapore company says its Lakehouse runs analysis on a customer's own connected data in place, so brand data teams can focus on the questions, not on building and running the systems underneath them SINGAPORE, Aug. 10, 2026 /PRNewswire/ --&nbsp;Singdata has become one of the founding ecosystem partners of Geene 2.0, a next-generation enterprise AI commerce ecosystem platform launched as a SaaS product by Synagie, the digital commerce and technology brand of Hong Kong-listed Synagistics Limited. Geene 2.0 has 12 founding partners in total, including Synagie itself, and is scheduled for commercial launch on Aug. 8, 2026. Alongside Singdata, the other partners are BytePlus, China Mobile International, FLY Entertainment, Mei Ah Entertainment, DataCloud, Yiwise, Zeneva, DU-MAS, International Brand Centre and Masverse. <div class="PRN_ImbeddedAssetReference" id="DivAssetPlaceHolder1" style="TEXT-ALIGN: center; WIDTH: 100%"> <a href="https://mmx.prnasia.com/media/MS1965012/20260805221901EDT_image_1.jpg?id=OA2829364&amp;p=medium600" target="_blank" style="color: #0000FF"><img src="https://mmx.prnasia.com/media/MS1965012/20260805221901EDT_image_1.jpg?id=OA2829364&amp;p=medium600" title="" alt="" /></a> </div> Building a Trusted Data Ecosystem Synagie defines Geene 2.0 as a &quot;trusted AI commerce&quot; ecosystem: rather than having enterprises cobble together a set of isolated AI tools, the platform splits the work across five layers — analysis, strategy, content, execution and trusted verification — each handled by a specialized partner. Within that ecosystem, Singdata takes on the data layer, handling three recurring, high-frequency tasks: automated generation of business-intelligence reports, financial process automation, and automated collection of market intelligence. According to Co-founder and CEO Ethan Yu, operations staff no longer need to build fixed report templates in advance. A single question in natural language can surface sales trends or inventory changes, and repetitive work such as downloading reports and reconciling statements can be handed to AI as well. &quot;A brand's operations team used to spend hours every day in spreadsheets pulling reports, reconciling numbers and tracking competitors. Now, about 90% of that repetitive work can go to AI,&quot; Yu said. &quot;Tell the system what you want to see — for example, how short-video exposure and offline sales tracked over the past three months — and the report is ready within minutes.&quot; Data boundaries are something Singdata keeps coming back to, and Yu's way of putting it is plain: &quot;Singdata builds the kitchen and the equipment in it, so customers can focus on the chef's skill and the quality of the dish, not on building the stove,&quot; he said. &quot;A mature company's data team is the chef. They already know how to cook. Our tools just help them cook better.&quot; Singdata said this division of labor is not just a promise but a design choice built into the architecture. Its Lakehouse, powered by its self-developed Generic Incremental Compute engine, runs analysis directly on a customer's already-connected data, in place, without the customer needing to worry about how the underlying infrastructure is built. &quot;Data intelligence is built on the customer's own data,&quot; Yu said. &quot;Seeing the insight should never require the chef to design the kitchen or the stove.&quot; Infrastructure Is Its Own Craft — What Singdata Does Next Singdata is a Singapore-headquartered AI-and-data infrastructure company, with customers across Asia-Pacific spanning the internet, automotive, logistics and education sectors. Its core technology pairs a self-developed Generic Incremental Compute engine with a lakehouse architecture. According to the company, enterprises trying to put AI to work typically hit one of two bottlenecks: whether their data is directly readable and usable by AI systems (AI-ready), and whether it can be processed and retrieved in real time. Generic Incremental Compute is built to address both, making multi-modal enterprise data AI-usable and able to support large language models in reasoning and decision-making. At the product level, Singdata Lakehouse runs across seven cloud platforms, including AWS, Google Cloud, and Alibaba Cloud. The company is a core contributor to Apache Iceberg, the open table format for data lakes, and says the architecture keeps customers in full control of their own data. Southeast Asian e-commerce logistics provider Ninja Van used it to migrate off its legacy systems without disruption. The rest of the Geene 2.0 ecosystem includes partners responsible for AI models, content production, livestreaming and blockchain verification, each covering a different layer. Singdata's focus stays on the data layer: organizing and ingesting a brand's scattered data is what the rest of the ecosystem depends on to function.

Singdata Named Founding Data Partner in Synagie's Geene 2.0, Takes On the Infrastructure Layer for Brands

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