Image credit: Curium Life
In a laparoscopic operation, the surgeon never touches the tissue. Everything happens through a 2D camera feed: instruments enter through small ports, and the surgeon has to judge depth, distance and the size of anatomical structures from a flat image — the way you would thread a needle wearing one eye shut. According to a Bengaluru startup led by a practising surgeon, the measurement error when surgeons estimate with rulers, threads and calipers averages around 30%. Its answer is software that measures anatomy in real time, while the operation is still under way.
The company is Curium Life, founded in 2023 by Dr Vinayak S Rengan, a paediatric and neonatal surgeon at Dr Mehta’s Hospitals in Chennai, together with Balachandran Seetharam (Balu Seetharam) on the business side and Mani R leading technology. Rengan’s clinical background is the company’s origin story: after operating on newborns hours old in one of India’s highest-volume paediatric surgery units, he decided the operating room needed a new kind of instrument — one that sees and measures.
SurgiMeasure: measurement as a real-time overlay
Curium’s first product is SurgiMeasure, which uses computer vision, deep learning, anatomical segmentation and depth estimation to give surgeons live anatomical measurements during laparoscopic and robotic procedures. The system is designed to be hardware-agnostic, working with the monocular laparoscopic cameras that remain the most widely used format in minimally invasive surgery, rather than being tied to one vendor’s equipment.
The company’s figures for the platform: 98% instrument-segmentation accuracy, real-time inference at 30 frames per second, and end-to-end latency under 300 milliseconds — fast enough, the company says, for the measurement layer to keep up with the surgeon’s hands. Rengan’s pitch is a navigation metaphor: SurgiMeasure should act as a kind of Google Maps for the abdomen, telling the surgeon what can be cut, what must not be, and how much margin lies between the two.
Proof it works
The system has moved beyond the lab. According to the company, SurgiMeasure has been deployed in live operating rooms and tested in eight live surgeries at Dr Mehta’s Hospitals in Chennai. Separately, a peer-reviewed study published in 2026 in the Journal of Abdominal Wall Surgery by Rengan and colleagues demonstrated automated multi-structure CT segmentation for ventral-hernia surgical planning — the disclosure statement confirms Rengan is the founder of Curium Life Tech and the company supported the work, which is as close to independent technical validation as the startup has so far.
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The traction is modest but real for a nine-member team: more than 50 expert surgeon collaborators across India, the US and other regions, over 20 letters of intent for structured data acquisition, and a win at the Johnson & Johnson Polyphonic Surgical AI Challenge 2026. In October 2026 the company was named to YourStory’s Tech30 cohort, and it was selected for the University of Chicago Polsky Center’s first India Deep Tech Accelerator cohort.
The bigger bet: a foundation model for surgery
Measurement is the wedge, not the destination. Curium says its long-term plan is a surgical foundation model trained on structured intraoperative data — an AI system that assists surgeons across procedures and specialities rather than a single-purpose tool. The current roadmap covers eight procedure families: hepatobiliary, gynaecology, urology, thoracic, abdominal, colorectal, bariatric and hernia surgery. The go-to-market strategy has also sharpened: instead of selling to hospitals directly, Curium is pitching its intelligence to laparoscopic and robotic surgery OEMs, aiming to embed it in the hardware platforms surgeons already use.
What would make this real
The honest caveats matter here. Curium is pre-revenue and pre-launch: the company has raised about Rs 2.5 crore through grants, friends and family and bootstrapping, and is now raising a Rs 7.5 crore pre-seed round. Commercial launch in India is planned for mid-2027 and in the US for 2028, subject to regulatory approvals — and Indian medical-device regulation has not traditionally been kind to fast timelines. The headline technical numbers are the company’s own; the Frontiers paper covers CT-based planning segmentation, not the real-time intraoperative system, and its authors note the work needs rigorous prospective validation of measurement accuracy and impact on patient outcomes.
Still, the pedigree is unusual: a startup where the founder still operates, the clinical collaborators are co-building the data set, and the AI lead sits alongside IIT Madras’ Prof Ganapathy Krishnamurthi. Most surgical-AI efforts are tied to proprietary hardware or single procedures. Curium’s bet is that the measurement problem — the one that shows up in every single operation — is the right foundation for a general surgical-intelligence layer. If the latency, accuracy and regulatory hurdles all clear, the operating rooms of 2028 may do their measuring the way cars now park: with the machine watching.
