SynQRemote Agent

Field work such as civil engineering, construction, and equipment inspection has heavily relied on the experience and knowledge of skilled workers, and difficulties are being encountered in the transfer of technology due to the aging and shortage of manpower.

Meanwhile, in the event of a problem in the field, unskilled workers have difficulty responding immediately, resulting in frequent calls to superiors or secondary visits, leading to inefficiency. Even if there is a work manual, it is difficult to apply it to the field situation, and in environments with unstable connections such as remote areas or tunnels, it is difficult to receive real-time support from the central office.

In short,“A way for even beginners to handle work accurately like veterans and accumulate knowledge”was needed. SynQRemote Agent aims to solve these problems by providing an AI assistant for field workers, thereby increasing safety and business continuity, and accumulating skilled know-how that has been buried in individuals as data.

SynQRemote Agent is an AI co-pilot that runs in a smartphone browser and can be used by simply touching a link without installing an app or logging in. When a worker points a smartphone camera at equipment or explains the situation verbally in the field, the AI immediately provides visual/audio feedback to guide inspection points, work procedures, and hazard warnings.

A distinctive feature is that it is optimized for use even in places with poor network connections; basic functions operate with browser cache and on-device computation even inside tunnels or in mountainous areas.

In addition, this system converts voice, video, and checklist interactions into structured data in real time, automatically creating work reports and accumulating records. Through this, *tacit knowledge* that previously existed only in the minds of skilled workers can be left as company assets, and the AI learns and becomes a self-reinforcing system that responds more intelligently to the field as time passes.

Existing remote support solutions mainly rely on video calls with experts, but SynQRemote Agent is fundamentally differentiated in that AI responds primarily, reducing the burden on manpower and learning on its own. Regional specialization such as Japanese field terminology is also a strength (first developed in Japan).

This solution is a B2B SaaS, and the main targets for adoption are construction companies, railway/road public corporations, and equipment maintenance companies.

For example, large construction companies can have their field engineers use this system to enable even beginners to perform high-quality inspections and to digitize know-how before skilled workers retire. Facility management companies can also use it for new employee training to reduce work errors and increase efficiency.

The cost is paid by companies/organizations, and QUANDO earns revenue in the form of annual licenses or cloud subscriptions. Field workers do not purchase it directly, but use it as members of the adopting company.

In addition, there is a prospect of B2G demand as it may be introduced on a national scale for public infrastructure management in the future.

The initial version is tailored to the Japanese construction/infrastructure environment, but it can be applied to field sites in other countries overseas simply by changing the language pack and manual knowledge base. As the shortage of skilled workers and the problem of aging infrastructure management are common worldwide, the market can be expanded by cooperating with local partners for localization.

Technically, it is easy to deploy because it is web-based, and it can be linked to other companies' ERP/management systems with modular APIs. However, AI models such as field voice recognition require local language, dialect, and domain data acquisition, so a learning period is required for each entry.

In terms of regulations, compliance with construction safety regulations and data security (when uploading field videos to the cloud) are issues, but rather, it may be supported in line with the government's digital transformation policy. In addition, if this concept is expanded to Industry 4.0 fields such as manufacturing equipment inspection and logistics warehouse work support, the target industry will increase significantly.

In summary, it has the potential to grow into a universal field AI assistant platform that is not limited to specific countries or industries.

Introduced to the international stage with the CES 2026 Innovation Award in the Artificial Intelligence category, it was evaluated as a *"solution for the Labor 3.0 era."* The judges highly praised the easy execution with a browser, offline environment support, and knowledge dataization, and commented that it realized a *"digital twin of the field."

In Japan, PoCs have already been conducted with construction technology research institutes to verify the completeness, and it will also participate in the 2025 Osaka Expo infrastructure management demonstration project.

Regarding the technical completeness, voice recognition and video interpretation accuracy under field noise are continuously being improved, but there is real user feedback that *"it is much better than nothing."* Market expectations are quite high as a DX solution for traditional industries, and there is news that it is receiving love calls from Asia, Europe, and other regions outside of Japan.

However, there is also a conservative view on *"how much field safety should be entrusted to AI,"* so initial adoption is expected to be used as a step to assist existing processes. Overall, it is accepted as a solution with a clear awareness of the problem rather than an overestimation, and the analysis is that changes in the field culture are more important than technology.