Company
Daibeats
What we do
Healthcare AI — ECG-based glucose estimation
Founded
2026
Location
India
Stage
Research & product validation
Funding
Bootstrapped
Legal status
Not yet incorporated
Contact
mdbasit@daibeats.comGlucose estimation from ECG.
Checking blood glucose usually means a finger-prick or a sensor inserted under the skin. That cost and discomfort limit how often people test, and many people with diabetes remain undiagnosed. Daibeats is developing technology that estimates glucose from the electrocardiogram (ECG), a signal already recorded by hospital monitors, clinical ECG machines, and a growing number of wearables.
Our approach combines heart rate variability and ECG waveform features with machine learning models trained with safety-aware objectives, so that errors in clinically dangerous glucose ranges are weighted more heavily. We are building software rather than new hardware.
Our first users will be research and clinical partners who need to analyse ECG and glucose data together. Over time, we aim to develop this into a practical healthcare product, following the clinical evidence and regulatory steps that requires. How the technology works →
From research to startup.
Daibeats builds on research into ECG-based glucose estimation that began before the company existed. That work was carried out by Md Basit Azam as doctoral research in the Department of Computer Science & Engineering, Tezpur University (Assam, India), and produced the publications listed on our publications page, including a 2025 arXiv preprint and a 2026 peer-reviewed paper in BMC Medical Informatics and Decision Making.
In 2026, Daibeats was founded as an independent startup to turn this research into a practical healthcare product. The company is bootstrapped and not yet incorporated.
Company and research lab.
Daibeats is an independent startup, not a university lab. The technology originates from research in ECG signal intelligence by the founder at Tezpur University, carried out with co-author S. I. Singh. We cite that academic work openly, and the people credited on it, rather than presenting it as company output.
Earlier research outputs that appear on this site, including papers dated before 2026, are the research foundation the company builds on. They are not products or commercial results of Daibeats.
Who is behind Daibeats.
Md Basit Azam
Founder & Lead Researcher, Daibeats
Md Basit Azam is a PhD researcher in the Department of Computer Science & Engineering at Tezpur University, working on machine learning for physiological signals, with a focus on ECG-based glucose estimation and on the external validation of healthcare models.
At Daibeats, Md Basit Azam leads research and product development: clinical dataset engineering (MIMIC-IV, eICU, AI-READI), ECG feature pipelines, safety-aware model development, and validation.
Verify & connect
- Email: mdbasit@daibeats.com
- GitHub: github.com/mdbasit897 ↗
- arXiv preprint (2025): When Validation Fails: Cross-Institutional Blood Pressure Prediction a… ↗
- BMC Med. Inform. Decis. Mak. (2026): Re-evaluating heart rate variability biomarkers for glucose sensing: t… ↗
Research & product validation.
Daibeats is developing and validating its ECG-based glucose estimation technology using clinical and wearable datasets. We have no commercial customers yet; our focus now is on strengthening the evidence through external and prospective validation.
Daibeats technology is under research and validation. It is not a medical device and has not received regulatory approval.