SigTuple builds intelligent screening solutions to aid diagnosis through AI-powered analysis of visual medical data.

How SigTuple helps


  We’re building an artificial intelligence (AI) platform called Manthana (मंथन) which helps us analyse visual medical data efficiently. Manthana has enabled us to work on five major high-volume, screening processes of the healthcare industry – analysis of peripheral blood smears, urine microscopy, semen, fundus & OCT scans and chest x-rays.

Shonit™ : is a complete peripheral blood smear analyser solution which automates the routine tasks like differential counts. Additionally, it provides a screening solution for various parasitic infections like malaria and disorders like anaemia. It starts by capturing images of blood smear slides with a phone fitted on a microscope. The images are analysed on cloud using state of the art image processing and deep learning techniques. Finally it generates reports containing differential blood counts, visualisations on various blood metrics and suggestions about any abnormalities. The report can then be reviewed by pathologists on any net connected device, from anywhere in the world, making this product useful for areas having a dearth of specialists.

Status : Shonit has undergone 3 clinical validations and is being used in a closed beta by our partners.

Shrava: After serum chemistry and blood, urine analysis is the most common pathology test. Our urinalysis solution detects substances like crystals and casts, cellular material like epithelial cells, RBCs and WBCs, and also calculates related volumetric parameters. The presence of these bodies in urine are indicative of a host of metabolic and kidney disorders. In urine microscopy the sample is liquid and multilayered unlike blood. This poses a greater challenge in the image capturing process.

Status: Shrava is nearing clinical validation stage

Aadi – Semen analysis is one of the core aspects in infertility investigations for measurement of male fecundity in clinical andrology. Our capability, Aadi, uses state-of-the-art artificial intelligence techniques to estimate pivotal parameters of ejaculated human spermatozoa like progressive motility, concentration and morphological characteristics. These parameters aid andrologists to correlate with clinical findings and help them to predict the ability of the spermatozoa to fertilise the oocyte.

Status: Aadi is nearing clinical validation stage

Dhrishti (Retinal Scans Analysis) – The scope of the Retinal Scan Analysis solution covers two major imaging modalities used by ophthalmologists to examine the inner eye (retina).

  1. Fundus Photography: This captures images of the fundus (back wall) of the eye – covering the retina, the optical disk and the macula. This is the more popular screening procedure of the two.
  2. Optical Coherence Tomography (OCT) Images: This provides high resolution cross sectional views of the internal retinal tissue of the eye. This is a more recent development and hasn’t caught on as much as fundus photography, specially in developing countries like India.

This solution aims to use computer vision and artificial intelligence techniques to identify and localise base pathologies and abnormal structures in both fundus and OCT scans. These findings can be used to provide various diagnostic indications to the ophthalmologist about the patient.

Status: Retinal Scan analysis is in product development. The research phase is complete.

Chest X-Ray Analysis – The chest x-ray is the most common diagnostic scan performed in radiology. It reveals images of the heart, lungs, blood vessels, ribs, etc. We are building a screening solution for chest x-rays, which separates the normal cases from those having abnormalities. It points out the abnormalities (fractured ribs, lung infections, etc.) when present. The solution works on digital x-ray images from any standard x-ray machine.

Status: Chest x-ray analysis is in research.


Manthana was created, from ground-up, to be a continuously improving, automatically upgrading platform which enables digitisation, management and analysis of visual medical data. We aim at training various kinds of AI models on it, and wish to provide an insightful and interactive report to medical specialists.

Management & Discovery

 Ingestion, management and smart search on various kinds of medical visual data from multiple partners.

Processing & Analysing

Processing and analysing the visual data using varied computer vision and artificial intelligence techniques.

Native AI Support

All types of AI techniques are supported – statistical, machine learning and the recent advancements in deep learning space.

Annotation & Verification

Annotation of all unlabelled visual data and verification/correction of output predictions of various models by medical consultants.

Continuous Learning

Retraining of AI models with incremental corrections and additions to improve their performance.

Insightful Analysis

Analysing unseen medical images by invocation of one or many AI models on them and providing an insightful and interactive report to the doctor.



We dramatically improve speed, accuracy and consistency of a number of screening processes. Medical institutions can now serve more patients, with a significant reduction in human errors. Patients can now be more confident in the quality of healthcare delivery.



With a note-worthy technology invention that is changing the medical course in India, we have various publications in several medical and computing journals, documenting the significant impact the technology has on the medical industry. SigTuple also has filed for several patents in order to protect our technology.



A massive growth in the potential market for our technology has had the founders of Flipkart, venture capital giant Accel Partners, and other investors join us in our journey.


Advisors are the building blocks of the company and prove to be the strategic partners of SigTuple. Well known intellectuals belonging to industries, like Biotech, Healthcare, Law and Ethics, Clinical Planning, and Drug Development have joined hands with SigTuple to offer their best guidance.



Funding disruptive AI & ML Startups : CNBC TV 18 covers pi Ventures

pi Ventures

CNBC TV18’s Young Turks explores the thesis behind pi Ventures’s Investments and how two portfolio AI startups Niramai & Sigtuple are changing the healthcare space through disruptive use of AI.

30 Oct 2017
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With so many deadly diseases out there, you need a lot of medical tests. SigTuple, an Indian startup, wants to use AI to dramatically improve the speed, accuracy, and consistency of various screening processes. It wants to enable doctors to serve more patients, with fewer errors. And it wants to give patients more confidence in the medical system.

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23 Apr 2017
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Rohit Kumar Pandey, Tathagato Rai Dastidar and Apurv Anand want to solve the problem caused by the chronic shortage of trained medical practitioners. They are part of the team that founded SigTuple, an Indian startup that is building a platform to provide healthcare solutions by detecting different diseases using machine learning software. It promises to automatically analyze medical images and data to aid diagnosis.

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26 Feb 2017
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Economic Times

There is a growing gap between the number of patients and doctors across the world,” says Pandey. “Although a lot of work is being done to bridge the gap, there is a need for an intelligent, effective and scalable solution.” SigTuple is building a series of cloud-based screening tools to increase the efficiency and outreach of the healthcare industry.

Read More

03 July 2016


Come join hands with SigTuple if you’re creative, innovative, and passionate about making our world a healthier place.


The indiscriminate path to increase human knowledge can be found here. Our vision is to grow into an institution, make a change, and impact lives with awareness and forethought.
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