Bitmo Lab is testing an ultra-thin, bendable tracker built to fit inside items traditional trackers can’t
Updated
February 12, 2026 4:43 PM
Bitmo Lab's MeetSticker tracker. PHOTO: BITMO LAB
Location trackers have become everyday accessories for keys, bags and luggage. But as personal items grow slimmer and more design-focused — from minimalist wallets to passport sleeves and specialised gear — tracking them has become less straightforward. Most trackers are built as small, rigid discs that assume the presence of space, loops or compartments. That assumption has created a growing mismatch between modern product design and the technology meant to secure it.
Hong Kong–based startup Bitmo Lab is attempting to address that gap with a device called MeetSticker. Instead of the solid plastic casing typical of most trackers, MeetSticker is engineered to be flexible and ultra-thin, measuring just 0.8 millimetres thick. The bendable design allows it to sit within narrow compartments or along curved surfaces without altering the shape of the object. Rather than attaching to an item externally, it is intended to integrate discreetly inside it.
That structural shift is the core of the product’s proposition. By removing the rigid shell that defines conventional tracking hardware, MeetSticker can be placed in items that previously had no practical way to accommodate a tracker. Bitmo Lab states that the device connects through a proprietary network and a companion application compatible with both iOS and Android, positioning it as a cross-platform solution rather than one tied to a single ecosystem.
The implications extend beyond form factor. Objects without obvious attachment points — such as compact travel accessories or specialised tools — could potentially be monitored without visible add-ons. In doing so, the device broadens the scope of tracking technology into categories where aesthetics, aerodynamics or compact design matter as much as functionality.
Before moving toward retail distribution, however, the company is focusing on validation. Bitmo Lab has launched a five-week global alpha testing programme beginning February 9. Sixty participants will receive a prototype unit and early access to the app. According to the company, the programme is designed to assess durability, usability and real-world performance before a wider commercial release. Participants who provide feedback will receive a retail unit upon launch.
Such testing is particularly relevant for flexible electronics. Unlike rigid devices, bendable hardware must withstand repeated flexing, daily handling and environmental exposure. Early user data can help refine manufacturing processes and software optimisation before scaling production.
As with other connected tracking devices, privacy considerations remain part of the equation. Bitmo Lab has stated that data collected during the alpha programme will be used strictly for testing purposes and deleted once the programme concludes.
Whether flexible trackers will redefine the category will depend on how they perform outside controlled testing environments. Still, the introduction of a near-invisible, bendable tracking device reflects a broader shift in consumer technology. As everyday products become thinner and more design-conscious, the tools built to protect them may need to adapt just as seamlessly.
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A closer look at how machine intelligence is helping doctors see cancer in an entirely new light.
Updated
January 8, 2026 6:33 PM
Serratia marcescens colonies on BTB agar medium. PHOTO: UNSPLASH
Artificial intelligence is beginning to change how scientists understand cancer at the cellular level. In a new collaboration, Bio-Techne Corporation, a global life sciences tools provider, and Nucleai, an AI company specializing in spatial biology for precision medicine, have unveiled data from the SECOMBIT clinical trial that could reshape how doctors predict cancer treatment outcomes. The results, presented at the Society for Immunotherapy of Cancer (SITC) 2025 Annual Meeting, highlight how AI-powered analysis of tumor environments can reveal which patients are more likely to benefit from specific therapies.
Led in collaboration with Professor Paolo Ascierto of the University of Napoli Federico II and Istituto Nazionale Tumori IRCCS Fondazione Pascale, the study explores how spatial biology — the science of mapping where and how cells interact within tissue — can uncover subtle immune behaviors linked to survival in melanoma patients.
Using Bio-Techne’s COMET platform and a 28-plex multiplex immunofluorescence panel, researchers analyzed 42 pre-treatment biopsies from patients with metastatic melanoma, an advanced stage of skin cancer. Nucleai’s multimodal AI platform integrated these imaging results with pathology and clinical data to trace patterns of immune cell interactions inside tumors.
The findings revealed that therapy sequencing significantly influences immune activity and patient outcomes. Patients who received targeted therapy followed by immunotherapy showed stronger immune activation, marked by higher levels of PD-L1+ CD8 T-cells and ICOS+ CD4 T-cells. Those who began with immunotherapy benefited most when PD-1+ CD8 T-cells engaged closely with PD-L1+ CD4 T-cells along the tumor’s invasive edge. Meanwhile, in patients alternating between targeted and immune treatments, beneficial antigen-presenting cell (APC) and T-cell interactions appeared near tumor margins, whereas macrophage activity in the outer tumor environment pointed to poorer prognosis.
“This study exemplifies how our innovative spatial imaging and analysis workflow can be applied broadly to clinical research to ultimately transform clinical decision-making in immuno-oncology”, said Matt McManus, President of the Diagnostics and Spatial Biology Segment at Bio-Techne.
The collaboration between the two companies underscores how AI and high-plex imaging together can help decode complex biological systems. As Avi Veidman, CEO of Nucleai, explained, “Our multimodal spatial operating system enables integration of high-plex imaging, data and clinical information to identify predictive biomarkers in clinical settings. This collaboration shows how precision medicine products can become more accurate, explainable and differentiated when powered by high-plex spatial proteomics – not limited by low-plex or H&E data alone”.
Dr. Ascierto described the SECOMBIT trial as “a milestone in demonstrating the possible predictive power of spatial biomarkers in patients enrolled in a clinical study”.
The study’s broader message is clear: understanding where immune cells are and how they interact inside a tumor could become just as important as knowing what they are. As AI continues to map these microscopic landscapes, oncology may move closer to genuinely personalized treatment — one patient, and one immune network, at a time.