Turning AI Innovation into Sustainable Profitability: Deepexi Technology (1384.HK) Delivers Surging Revenue, Quarterly Profitability, and a Differentiated Enterprise AI Platform

HONG KONG SAR – Media OutReach Newswire – 27 August 2026 – In an era when enterprise software valuations are being fundamentally repriced by the rise of agentic AI, Deepexi Technology Co.

, Ltd. (1384.HK) has emerged as a rare counterexample: a pure-play enterprise AI platform that is delivering both technology leadership and bottom-line profitability. According to the company's first interim results following its public listing, Deepexi recorded a 115% year-over-year surge in revenue for the first half of the year, powered by a 209% leap in core AI revenue and a decisive turnaround to quarterly GAAP profitability in the second quarter of 2026. This performance has earned the company "Buy" and "Overweight" ratings from multiple brokerages within its first year of listing.

Quarterly Profitability: A Rare Milestone in Hong Kong's AI Sector

In capital markets, ambitious visions must ultimately be backed by real financial performance—and Deepexi's interim results provide clear proof of execution.

For the first half of 2026, the company generated RMB 284.0 million in total revenue, marking a 115.0% year-over-year increase. Its AI business served as the primary growth engine, contributing RMB 226.0 million—an impressive 209.2% year-over-year surge—bringing AI revenue to 79.6% of total corporate turnover.

Even more noteworthy is the marked improvement in profitability. First-half gross profit reached RMB 160.0 million, up 120.5% year-over-year, with gross profit margin expanding to 56.5%. Crucially, during the second quarter of 2026, Deepexi posted a standalone quarterly net profit of approximately RMB 30.1 million, officially crossing the breakeven threshold.

In Hong Kong's technology sector, pure-play enterprise AI companies capable of achieving quarterly net profitability while sustaining high R&D investment remain exceptionally rare. This milestone underscores Deepexi's operational efficiency, scalable software delivery, and self-sustaining monetization engine.

This scarcity value is equally evident in the company's revenue composition and vertical reach. Industrial manufacturing accounted for more than 50% of total revenue, while retail and consumer goods contributed 30%, alongside expanding footholds in healthcare and smart transportation. In manufacturing, for example, equipment troubleshooting and predictive maintenance involve dense engineering schematics, real-time IoT sensor telemetry, and extensive historical maintenance logs—all of which Deepexi translates into structured logic that AI models can readily interpret. This deep vertical expertise and proprietary data accumulation create a formidable competitive barrier that general-purpose AI vendors cannot easily match.

Beyond the "SaaSpocalypse": Deepexi's AI-Native Platform Defies the Software Valuation Reset

The first quarter of 2026 witnessed what market observers have dubbed the "SaaSpocalypse"—a tectonic shift in which approximately $2 trillion in market capitalization was erased from B2B software equities, driven by a fundamental fear that agentic AI would cannibalize the traditional per-seat licensing model. The iShares Expanded Tech-Software ETF (IGV) plunged nearly 21% year-to-date, and enterprise software multiples (EV/Sales) cratered from a 5.6x average at the end of 2025 to 4.2x by mid-March.

Investors have pivoted decisively toward AI-native infrastructure—companies that manage the data and underlying plumbing of autonomous systems—while penalizing traditional application-layer SaaS vendors reliant on human-centric interfaces. As a recent Windsor Drake analysis notes, "AI-native agentic platforms clear 14x to 22x revenue, with private rounds at 20x to 30x," while legacy standalone RPA trades at just 2.5x to 5x. The market is now rewarding AI-native architecture and measurable workflow ownership.

Deepexi sits squarely on the winning side of this divergence. Unlike traditional SaaS vendors whose revenues are tied to human seat counts—and thus vulnerable to agentic displacement—Deepexi's token-based, consumption-driven model aligns directly with the agentic AI future. The company's DeepWorks enterprise Agent platform does not sell per-seat licenses; it sells AI productivity, enabling enterprises to deploy autonomous agents that replace repetitive administrative work, not software seats. As the market shifts from "AI as a feature" to "AI as a replacement," Deepexi's business model is structurally insulated from the seat-compression forces that have punished legacy software vendors.

Focus on Enterprise AI Applications and Proprietary Domain Data

To ensure AI truly meets real-world enterprise demands, generic foundational models are insufficient on their own. Deepexi's core competitive edge lies in its specialized "Data + AI" dual-engine architecture, anchored by the FastData enterprise data intelligence platform, the FastAGI agentic AI suite, and the Deepexi Enterprise Large Model Platform, supported by its proprietary Deepology ontology dataset containing over 2,000 vertical industry skills.

At the foundational layer, the FastData platform—powered by the FastData Foil fusion engine—acts as an intelligent lakehouse that tokenizes structured, semi-structured, and complex unstructured enterprise data into standardized formats ready for large model training and inference. Building upon this data foundation, the FastAGI platform and DeepWorks Enterprise Agent Platform provide organizations with a flexible, modular AI operating system.

Featuring a pluggable architecture, the platform connects seamlessly to leading open-source foundation models such as DeepSeek and Zhipu AI, giving enterprise clients complete autonomy while eliminating vendor lock-in. This "model-agnostic" approach is a key differentiator in an environment where enterprises increasingly demand flexibility to choose the best model for each use case, rather than being locked into a single provider.

Through native Model Context Protocol (MCP) frameworks and specialized agents—ranging from operational decision-making agents to productivity and autonomous workflow execution agents—Deepexi embeds intelligence directly into core business operations. DeepWorks is fully integrated with mainstream workplace collaboration suites such as DingTalk, Feishu, and Tencent Meeting, allowing employees to summon AI copilots directly for automated weekly reporting, data synthesis, and cross-departmental coordination—effectively turning AI into an indispensable daily productivity tool.

In an enterprise AI market where 42% of organizations already have AI agents in production and 72% are deploying across production and pilots combined, Deepexi's proven, governed agentic workflows are no longer an experiment—they are core infrastructure.

Strategic Partnership with Huawei Cloud: Tackling Compute and Data Bottlenecks

In the commercialization of enterprise AI, computing costs and access to high-quality domain data represent two of the industry's most critical bottlenecks. On August 12, Deepexi announced a strategic alliance with Huawei Cloud to jointly launch enterprise data intelligence solutions, providing strong operational backing for the company's long-term expansion.

The partnership combines the complementary strengths of both technology leaders. Huawei Cloud provides underlying Ascend AI computing clusters and distributed cloud infrastructure, while Deepexi brings its deep expertise in enterprise data governance, data tokenization, and vertical AI agent deployments. By integrating with Huawei's domestic Ascend compute clusters, Deepexi not only secures stable, long-term computing power but also significantly drives down token processing costs. This cost efficiency establishes ideal conditions for exploring usage-based, token-metered commercial billing models—precisely the kind of consumption-based pricing that aligns with the agentic AI future.

Crucially, falling AI costs are widely expected to accelerate enterprise adoption of autonomous agents. Deepexi's partnership with Huawei Cloud positions the company to capture this demand wave with a cost structure that improves as token volumes scale—a powerful margin-expansion dynamic that stands in stark contrast to the fixed-cost burden of traditional SaaS.

Strong Institutional Backing Highlights Long-Term Investment Value

Reflecting strong capital market confidence, Deepexi announced on August 17 the successful placement of 14,286,000 new H-shares at HK$35.00 per share, raising net proceeds of approximately HK$488.0 million. Successfully closing a sizeable placement amid broader market volatility demonstrates strong institutional recognition of Deepexi's proven business model, robust unit economics, and profitability trajectory.

The company's strategic shareholder structure provides a solid foundation for long-term growth. It is supported by prominent independent investors, including Hillhouse, 5Y Capital, and BAI, as well as industry-focused investors such as Shanghai AI. These partnerships enhance Deepexi's industry reputation, drive technological innovation, and strengthen its market competitiveness.

The newly raised funds are earmarked primarily for continuous R&D in next-generation enterprise agent systems and token productivity platforms—positioning the company to capture the $206.5 billion AI agent software market projected for 2026, which Gartner expects to grow to $376.3 billion in 2027.

Investment Thesis: Why Deepexi Stands Apart

1. AI-Native Architecture in an Agentic World. Unlike legacy SaaS vendors facing seat compression, Deepexi's token-based model is structurally aligned with the agentic AI future. The company doesn't sell software seats—it sells AI productivity.

2. Rare Profitability in Enterprise AI. Quarterly GAAP profitability at a 56.5% gross margin, with projected revenue CAGR of 95.5% through 2027, places Deepexi among the most financially disciplined enterprise AI companies globally.

3. Model-Agnostic, Vendor-Neutral Platform. In an environment where enterprises demand flexibility, Deepexi's pluggable architecture—supporting DeepSeek, Zhipu, and other open-source models—eliminates lock-in and captures value regardless of which foundation model wins.

4. Proprietary Data Moat. With over 2,000 vertical industry skills and deep expertise in manufacturing, retail, healthcare, and transportation, Deepexi's domain-specific data capabilities create barriers that general-purpose AI vendors cannot replicate.

5. Strategic Compute Partnership with Huawei Cloud. Long-term, cost-effective compute access, combined with token-metered pricing models, positions Deepexi for sustained margin expansion as token volumes scale.

6. Institutional Validation. Backing from top-tier investors and a successful HK$488 million placement amid market volatility signal strong institutional confidence in Deepexi's business model and growth trajectory.

The enterprise AI market has decisively shifted from early conceptual exploration into a new era of commercial execution and tangible financial delivery. Backed by mature product suites across FastData and FastAGI, proprietary vertical ontologies, strategic cloud partnerships, and an official transition to net profitability, Deepexi Technology has proven that enterprise AI can deliver both transformative technology and sustainable profits.

Hashtag: #DeepexiTechnology

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About Deepexi Technology

Deepexi Technology is China's leading provider of enterprise large model AI application solutions. Through its FastData enterprise data intelligence solution and FastAGI enterprise AI solution, it empowers enterprises to integrate their data, decisions and operations efficiently at scale. Deepexi ranked fifth in China's enterprise large model AI application solution market in terms of revenue in 2024. Its solutions have achieved large-scale commercialization across multiple verticals, including consumer goods, manufacturing, healthcare and transportation. As of June 30, 2025, Deepexi Technology served a cumulative total of 283 enterprise customers across various industries.

This press release contains forward-looking statements that involve risks and uncertainties. Actual results may differ materially from those projected. The company undertakes no obligation to update any forward-looking statements.