Kuailu Technology launches the KuWork enterprise-level AI work partner platform
As the implementation of AI in enterprises accelerates, most players are focused on competing for model capabilities, while Fast Heron Technology targets the long-ignored pain points at the enterprise execution layer, launching KuWork, an enterprise-level AI work partner platform, which defines a new paradigm of human-machine collaboration in enterprises with the brand-new "AI Work Layer", enabling AI to truly integrate into existing office systems of enterprises and solve business bottlenecks. Fast Heron Technology has accumulated 7 years of experience in enterprise scenario systems covering sales management, financial management, human resource management, administrative management and conferences, with pain points of office scenarios from thousands of enterprises and a large corpus of business scenarios accumulated, laying a solid foundation for KuWork to connect traditional systems with AI. Dong Ting, General Manager of Products at Fast Heron Technology, is a core operator of the Experian and Alibaba data middle platform and AI middle platform, who has witnessed the construction of a 10-billion-level platform from 0 to 1. As a serial entrepreneur, the data middle platform and Bot Framework projects he previously built have received financing of tens of millions of RMB.
1. Turn every AI task into organizational asset
The birth of KuWork stems from the insistence at the early founding stage of Fast Heron Technology: tools should adapt to people, rather than people adapting to tools. Since its establishment, Fast Heron Technology has targeted the one-stop intelligent office track. With long-term accumulation of data interconnection, the team quickly seized the opportunity when the AI wave arrived, responding to customer demands faster than traditional software enterprises, and officially launched the KuWork project in July 2026.
At present, enterprise office is generally faced with the pain point of "multiple systems but no interconnection": growing enterprises often deploy seven or eight sets of systems such as CRM, ERP and OA, and rely entirely on employees as "human routers" — manually copying data across systems to assemble forms, manually modifying orders across systems, and inconsistent statistical calibers of data output from multiple departments. These bottlenecks are not caused by insufficient model capabilities, but by the lack of a layer that connects methods, execution, responsibilities and organizational memory into a complete link: whether AI can enter existing systems, complete tasks safely and controllably, and return results to people. KuWork is built exactly for this layer — the AI Work Layer for enterprises, which enables trainable organizational methods, governable AI collaboration and compoundable enterprise capabilities, and trains the work methods of enterprise employees into reusable AI workforce.
Different from traditional AI assistants or development platforms, the technological and product innovations of KuWork center on the precipitation of enterprise organizational capabilities. Users start with real tasks: after an employee completes only one work demonstration, KuWork can extract the steps, rules, tools, acceptance standards and manual review points from it, to generate a governable organizational Skill. A Skill is not a simple prompt, but a "work charter" that defines how to do a task, to what standard, and what cannot be done. Meanwhile, it supports multiple Agents to share task status, and manual review of key nodes. The results and feedback of each execution will be precipitated as organizational memory, forming a closed loop of "task execution - review and calibration - memory precipitation - capability enhancement", turning every AI task of the enterprise into the accumulation of organizational assets, rather than a one-off disposable output.
KuWork supports two deployment methods: SaaS and private deployment, which can connect to foundation models and various existing systems of enterprises. Meanwhile, Skills and organizational memory are stored independently of the underlying model, so model replacement will not affect the continuous precipitation of the enterprise's context, methods and governance capabilities, solving the core pain point in current AI implementation that "AI output grows but enterprise capabilities do not accumulate". Different from market players that focus on the breadth of tasks, KuWork focuses on the depth of organizational capabilities. Its core advantage comes from 7 years of scenario-accumulated business data and pain point cognition, which can quickly connect traditional systems with AI, enabling AI to directly enter systems to complete tasks.
2. Market Space and Business Model
In terms of the market environment, current enterprise generative AI expenditure has increased 22 times in two years. According to a survey by Menlo Ventures, global enterprise GenAI application layer expenditure reached 19 billion US dollars in 2025, accounting for more than 50% of the total enterprise GenAI expenditure. 81% of managers plan to deeply integrate Agents into their enterprise AI strategy in the next 12 to 18 months, and 76% of enterprises choose to purchase AI solutions rather than build them on their own. The procurement window has opened, while the category standards have not yet been finalized, and there is a clear demand gap in the market. According to IDC's forecast, global AI expenditure will reach 632 billion US dollars in 2028, with a compound annual growth rate of 29% from 2024 to 2028. The first launch market in China can cover 30,000 target organizations, corresponding to an annual contract value scale of 15 billion to 60 billion US dollars, presenting a broad market space.
KuWork is currently in the internal test stage, where original long-term cooperative clients are invited to experience the product, with focus on verifying the task success rate, completion cycle and the reduction of manual links in benchmark scenarios. The first batch of verification focuses on two typical scenarios with complex collaboration and many manual links: manufacturing production scheduling and cross-border e-commerce order modification. In the manufacturing production scheduling collaboration scenario, the goal is to convert the original production scheduling process that requires manually copying data and assembling forms across four systems including ERP, MES, WMS and CRM, into a collaborative delivery mode where KuWork automatically pulls data, assembles and merges data according to rules, and humans conduct the final review. For cross-border e-commerce order modification, the goal is to convert the link that requires manual synchronization of multiple systems when a customer modifies an order, into automatic synchronization of multiple systems after one single modification, with humans only checking the results. After the internal test is completed, quantifiable comparison indicators of task cycle and error rate will be formed to verify the implementation path of "AI promotes work, and humans are responsible for judgment".
In terms of business model, KuWork adopts a three-tier progressive logic: the first tier is priced aligned with "workload", charging based on the number of tasks promoted by AI and the output results, which is different from the traditional SaaS seat-based charging, so that enterprises only pay for actual value. The second tier realizes high user retention relying on the precipitation of skill assets: the longer an enterprise uses the product, the more exclusive work methods it accumulates, and the higher the migration cost will be. The third tier follows the path of "single scenario verification - skill precipitation and reuse - full organization expansion", and the customer unit price increases naturally as value is delivered. No details of the project's current financing have been disclosed. Fast Heron Technology plans to complete the verification of benchmark scenarios first, then gradually replicate and expand across the whole organization, complete verification in the Chinese market first, and then gradually expand to the Asia-Pacific, European and American markets.
Looking at the product and business layout of Fast Heron, Dong Ting said that from SaaS to the AI work partner platform, the team has always adhered to the original aspiration of "tools serve people, and capabilities are precipitated to the organization". AI is not meant to replace people, but to liberate people from the repetitive "human router" work, allowing people to focus on making judgments, while keeping the experience of employees truly in the organization. We believe that when people's methods can be learned, executed and governed, AI will truly become a reusable productivity for the organization, which is also the core value that KuWork aims to bring to all enterprises.