See-Mode Technologies, a medtech startup based in Singapore and Australia, has raised $7 million in a financing round.
The funding round was led by MassMutual Ventures Southeast Asia. Also participating were existing investors Blackbird Ventures, Cocoon Capital, Entrepreneur First, and SGInnovate, along with a group of angel investors.
The startup seeks to improve stroke prediction with artificial intelligence (AI)-based medical software and will use the investment to expand its commercial operation to Europe and the U.S. in the coming year. See-Mode will also use the money to double its team, expand research and development, and increase its sales as well as business development team. See-Mode also seeks partnerships with research institutions around the world to support its research and development efforts.
See-Mode's debut software, Augmented Vascular Analysis (AVA), uses deep learning, text recognition, and signal processing technologies to assist clinicians in interpreting and reporting vascular ultrasound studies. The firm says using its technology to generate reports can reduce the report generation time from 20 minutes to less than a minute.
AVA is approved by the Singapore Health Science Authority and is commercially available in Singapore, with ongoing pilots in Singaporean and Australian hospitals. The software is pending regulatory approval in other regions, including the CE Mark in Europe and from the U.S. Food and Drug Administration (FDA).
Other than AVA, See-Mode is also developing software to detect plaque using machine learning and to identify high-risk blood flow using computational modeling. See-Mode has completed proof-of-concepts for both with collaborators in Singapore and Australia. Multicenter clinical studies are now taking place across Europe and the U.S.
![Examples of ultrasound findings and techniques. (A) Images in a 39-year-old male patient with a mass in the left thigh. The mass is heterogeneous on the B-mode US image (compared with the patient in D) and showed increased microvascularity (superb microvascular imaging [SMI]) and shear-wave elastography (SWE) values. Undifferentiated pleomorphic sarcoma was diagnosed at biopsy (with pleomorphic rhabdomyosarcoma in surgical specimen). (B) Images in an 18-year-old male patient with a mass in the left leg. The mass is hypoechoic on the B-mode image, with no other findings suggestive of malignancy. The lesion is in contact with the cortex of the tibia, which is slightly irregular. CT revealed a doubtful anteromedial tibial erosion. The microvascular study demonstrated high vascularization, suggestive of malignancy. Periosteal Ewing sarcoma was diagnosed with both histologic and immunohistochemical confirmation. (C) Images in a 69-year-old female patient with a lump growing on the outside of the left leg. Multiple SWE examinations were performed (please note the high values obtained in the measurements, whereas the color map highlights the stiffness relative to adjacent tissues). SMI showed areas of increased vascularization to target for sampling. Undifferentiated spindle cell sarcoma was diagnosed at biopsy, with residual leiomyosarcoma in the surgical specimen after neoadjuvant therapy. (D) Images in a 56-year-old female patient with a mass in the right thigh. The mass is heterogeneous at both B-mode ultrasound (similar to patient A) and MRI (coronal T2-weighted spectral attenuated inversion recovery [SPAIR]; T1-weighted pre-contrast and postcontrast imaging), which even shows uptake after the administration of paramagnetic contrast material, which is traditionally suggestive of malignancy. Low values at SMI and elastography are suggestive of benignity. Spindle cell lipoma was diagnosed at biopsy, with atypical spindle cell lipomatous tumor in the surgical specimen.](https://img.auntminnie.com/mindful/smg/workspaces/default/uploads/2026/08/images-radiol250278fig2.APCFLSvX6p.jpg?auto=format%2Ccompress&dpr=2&fit=crop&h=167&q=70&w=250)