"AI+Inspection" - Equipping Testing Experts with an "Intelligent Auxiliary Brain"

2026-01-29 10:18:51

In the era of rapid technological development, artificial intelligence (AI) is penetrating various industries with a breakthrough momentum. As a key pillar in this field, the Laboratory Information Management System (LIMS), empowered by AI technology, is undergoing a profound transformation, thereby reshaping the entire new ecosystem of inspection and testing.

Preface: AI Reshapes the New Paradigm of Inspection
Traditional LIMS has played an important role in the daily operation and data management of laboratories, but a large number of manual operations are still required in some scenarios. For example, when new testing standards are introduced in the industry, it often takes a lot of time and manpower to adjust the LIMS system, which seems particularly passive in today's fast-paced development. In terms of data analysis, traditional LIMS mostly stays at simple data statistics, unable to conduct in-depth mining of massive testing data, making it difficult to discover the hidden trends and patterns behind the data and failing to provide strong support for laboratory decision-making.
To address the above issues, AI technology is helping to transform the inspection and testing industry, becoming the "super sensory organ" and "data auxiliary brain" for laboratory testing experts. The application of AI technology in the inspection and testing industry essentially equips professional testing personnel with more powerful "sensory organs" and more efficient "data processors". This frees professionals from a large number of repetitive and standardized data processing tasks, enabling them to focus on tasks requiring creativity and in-depth analysis, and optimizing the overall workflow.
Independently developed by Beijing SunwayWorld Technology Co., Ltd., the SunwayLink AI Application Development Platform integrates three core capabilities: supporting the rapid construction of generative AI applications for multiple scenarios, enabling efficient knowledge base management, and providing a plug-in management system for extending large language models. Its unique value lies in its seamless integration with enterprises' existing business systems and in-depth integration with SunwayWorld's low-code platform, jointly shaping a new digital and intelligent management paradigm for inspection and testing.
The platform is committed to becoming a strong partner for enterprises' intelligent transformation, providing one-stop solutions for various users who expect to solve business pain points, optimize decisions, and drive innovation through AI. The following are some intelligent application scenarios realized through the close integration of the SunwayLink AI Application Development Platform and the SW-LIMS system in the form of "AI+Inspection".

I. As a "Super Vision": Improving Testing Efficiency and AccuracyIn the field of food testing, the integration of high-speed scanners and AI image recognition technology enables multi-angle photography, intelligent identification and extraction of information from food outer packaging, and supports automatic data entry. This significantly improves the efficiency and accuracy of the sample acceptance process, effectively solving the pain point of excessive manual photography and data entry workload.
In the scenario of microscopic identification of Chinese medicinal materials, through the innovative development of the "AI-based Microscopic Image Identification of Chinese Medicinal Materials" function, the system can intelligently compare the images of Chinese medicinal material components obtained under a microscope with the standard library, automatically identify the varieties of Chinese medicinal materials, and further improve the accuracy of microscopic identification.

II. As an "Expert Auxiliary Brain": Building an Intelligent Quality Control and Audit System
Relying on the collaborative working mode of "AI pre-screening + expert review", AI, as a scientific tool, can quickly scan massive sample data, mark suspicious items, and assist experts in focusing on key areas for in-depth analysis.
For example, in the audit of inspection work, the "intelligent quality control of inspection result images" function can accurately identify repeatedly used instrument graph files, effectively preventing irregularities such as "reusing the same graph", and providing double guarantees for the authenticity and reliability of inspection results. In the report audit link, the "intelligent pre-audit assistant for compliance of test reports" uses AI technology to assist auditors in conducting compliance reviews, improving review efficiency and accuracy, thereby enhancing the overall inspection compliance and speed. Such intelligent pre-audit assistants have been applied in targeted scenarios such as sampling audits and test data audits.
It should be emphasized that "AI is a super assistant for scientists" - AI is always positioned as a tool, and experts are the core decision-makers. Its core value lies in undertaking basic work such as initial screening of massive data and repetitive standardized operations, thereby liberating expert resources and allowing them to focus on core links requiring in-depth judgment, such as complex sample analysis, result interpretation, and report review.

III. As a "Knowledge Steward": Driving the Intelligent Upgrade of Laboratories
What AI brings to modern laboratories is not simple information storage, but the systematic precipitation, intelligent association, and active empowerment of knowledge. By integrating historical test data, standard documents, and risk early warning information, AI can construct a professional knowledge graph, transforming the laboratory's intangible assets (data, experience, rules) into "institutional wisdom" that can be called at any time and continuously evolved.
For example, when abnormal data appears during the testing process, the system can automatically provide associated risk prompts and literature references, assisting experts in making more comprehensive judgments, and realizing in-depth mining of data value and active application of knowledge.
For instance, discovering that "the fluctuation probability of a certain indicator of raw materials from a specific origin increases significantly under specific humidity" forms forward-looking quality early warning knowledge. AI can form a case experience database from processed abnormal data, complex cases, successful solutions, and other information. When similar graphs or problems arise, it actively pushes historical cases and expert analysis ideas to assist in rapid decision-making.
In addition, realizing knowledge inheritance and standardization, and precipitating the experience and judgment logic of top experts into models, helps standardize and inherit testing methods and quality judgment, alleviating the pressure of talent and experience gaps.

IV. Core Value: Experts are Precious Wealth of the Testing Industry
"AI+Inspection" does not aim to build unmanned laboratories, but to free professionals from a large number of repetitive and standardized data processing tasks, reduce the repetitive work of experts, and allow them to focus on tasks requiring human wisdom. It reshapes an efficient, accurate, and forward-looking working mode in the testing industry, thereby improving testing precision and efficiency, optimizing process management, promoting service model innovation, strengthening decision support, and continuously moving towards an "intelligent laboratory" with in-depth human-machine collaboration.
Make professionals more professional and science more efficient - this is the real transformation that "AI+Inspection" brings to the inspection and testing industry.