At Photonics West in San Francisco, Tom Tiner from MV Pro sat down with Kevin from SinceVision to explore how advanced sensing technologies are moving from research environments into demanding industrial applications. The conversation highlighted SinceVision’s positioning in high-end imaging, the growing importance of accurate data for AI, and the steady expansion of 3D and high-speed vision into production environments
3 Key Messages
1. Precision Data Enables AI Success
SinceVision emphasises high-accuracy sensing as the foundation of effective AI vision systems, reinforcing that data quality remains critical to machine learning performance.
2. Advanced Imaging Is Expanding Across Industries
High-speed and 3D vision technologies are increasingly deployed in electronics, semiconductor, automotive, battery, and solar manufacturing for inspection and analysis.
3. Adoption Depends on Ecosystem Readiness and Knowledge
While technology is mature, infrastructure and user understanding continue to influence deployment speed, though industry awareness and adoption are steadily growing.
SinceVision operates across two complementary domains: scientific imaging and industrial precision sensors. Kevin explained that this dual focus allows the company to support both academic research and real-world manufacturing challenges. Its portfolio includes 3D profiler sensors, spectral confocal sensors, laser displacement technologies, and high-speed imaging systems designed for applications ranging from low-light research environments to high-accuracy industrial inspection.
“We’re a manufacturer focused on scientific imaging and industrial precision sensors,” Kevin noted, outlining how the company bridges laboratory innovation with production deployment.
A central theme of the discussion was performance and accuracy. Kevin highlighted SinceVision’s emphasis on high-resolution 3D laser profiling, with sensors capable of capturing thousands of measurement points across a field of view. This increased data density enables more precise surface inspection and dimensional measurement, making the technology particularly relevant for electronics, semiconductor manufacturing, automotive components, lithium battery production, and solar panel inspection.
Beyond static inspection, SinceVision’s high-speed imaging capabilities support dynamic analysis applications such as particle tracking, motion analysis, and automotive crash testing. These use cases reflect the growing need for vision systems that can capture fast-changing events while maintaining measurement fidelity.
Beyond static inspection, SinceVision’s high-speed imaging capabilities support dynamic analysis applications such as particle tracking, motion analysis, and automotive crash testing. These use cases reflect the growing need for vision systems that can capture fast-changing events while maintaining measurement fidelity.
Tom also raised a broader industry question: how machine vision technologies transition from laboratory development into scalable production solutions. Kevin emphasized that SinceVision’s products are already designed for deployment in high-end industrial environments, but acknowledged that broader ecosystem readiness can sometimes lag behind sensor capabilities.
The conversation then turned to artificial intelligence, a recurring topic throughout Photonics West. Kevin provided a grounded perspective on AI’s role in machine vision, stressing that algorithmic advances must be supported by high-quality data acquisition.
“You need three fundamental factors with AI — data, algorithms, and processing power,” he explained. “We’re 100% involved on the data side.”
This emphasis on data highlights a critical industry reality: AI performance is ultimately limited by the quality and accuracy of input information. SinceVision’s strategy therefore focuses on capturing reliable, high-fidelity representations of real-world phenomena, enabling downstream analytics and AI models to operate more effectively.
Another topic addressed was deployment bottlenecks, including infrastructure constraints such as cabling, computing power, and system integration. Kevin suggested that while technology continues to advance rapidly, knowledge gaps among users and integrators can slow adoption, particularly in emerging areas like 3D sensing and high-speed imaging.
“The whole vision and imaging technology is still growing — both in technology and in people’s knowledge,” Kevin observed.
Despite these challenges, Kevin expressed confidence in continued industry growth. He pointed to expanding awareness of machine vision capabilities and increasing comfort with deploying advanced sensing solutions across a wider range of industries. This gradual normalisation of high-performance imaging is expected to accelerate adoption and unlock new application opportunities.
Overall, the interview reflects a broader shift in machine vision: the convergence of precision sensing, AI-ready data acquisition, and industrial scalability. SinceVision’s approach demonstrates how sensor innovation can enable both advanced research and production-grade inspection, while reinforcing the importance of system-level readiness and user understanding in achieving successful deployments.
As machine vision continues to evolve, the conversation underscores a key takeaway, future progress will depend not only on algorithmic advances, but on the ability to capture accurate, meaningful data from the physical world and translate it into actionable insight across industrial workflows.
Learn more at https://www.sincevision.com/
