Our team comprises of seasoned business-facing professionals, academics, and domain experts to add real value to the product and our customers.
Dev has close to 2 decades of experience in delivering data, insights and Artificial Intelligence (AI) engagements for global clients. He founded Converz with an aim to connect the healthcare community and add value by leveraging AI. His academic background of maths and computer science provided him with a perfect launch pad to understand the nuances of modern neural nets. This technical know-how complements his leadership skills to deliver stellar outcomes.
Joseph is a consultant cardiologist with interests in Cardiac Rhythm (arrhythmia) and function. He has Research experience in cardiovascular epidemiology, clinical trials, systematic reviews and meta-analyses. His current interests include collaborations in health research, public health and medical education. He is a keen technology enthusiast aiming to maximise value add to NHS and healthcare.
Sanjeeva is the lead for the Oxford University Hospitals Skull Base Surgery Programme. His clinical practice focuses on the surgical treatment of complex skull base lesions with open and minimally invasive techniques, and facial pain syndromes. His current research interests are in developing and integrating artificial intelligence technology into the skull base surgery service at Oxford. He is also working on the use of artificial intelligence in diagnosis and triage, smart phone technology in aiding diagnosis and robotic surgery.
Professor Fabio Cuzzolin founded Oxford Brookes’ Visual Artificial Intelligence Lab in 2012. Fabio has published more than 100 papers, is in the PC of all major machine learning and vision conferences and is executive committee member of a joint Huawei-SFU-British Columbia research centre. His expert research inputs on latest and greatest in AI helps us be at the forefront of technology.
Waqar has 13 years of experience leading financial roles for IT and healthcare enterprises. He is also a qualified chartered accountant. He keeps a close eye on company’s finances and helps with reporting and other financial activities.
Jim is a success entrepreneur who took his company RealTime Health through a successful trade sale. RealTime’s mission was to reduce the length of stay in acute hospitals through clinical process improvement and real time performance metrics and it was acquired by in 2012. He has extensive experience of commercial processes that work within the healthcare sector.
A Software Developer turned online marketer who is passionate about leveraging latest technology to unravel meaningful and deep marketing insights from data. Other interests include spirituality, meditation, beatboxing and Salsa dancing. Prior experience includes companies such as Microsoft. He leads all the marketing initiatives.
Prior to joining Converz, Rishab’s primary focus was developing supervised learning models on private data and product deployment. He has worked at the customer’s production unit in Japan and implemented AI models for real time data prediction, improving yield management. He also contributes to social causes by deploying technology. Recently he presented such work at the Building AI Through Collaborative Innovation (with NASA and Open Assembly) conference.
Rajesh has designed and delivered majestic user experience interfaces at UK based companies such as GSK, Shell, British Petroleum, British Gas and many more. He has more than 12 years of work experience and is an expert on all modern user interface technologies such as React.js, UI5 libraries. Since most of his work is in B2B space, he has also used enterprise UX design platforms to deliver awesome screens.
Our awesome products that maximise value through use of AI.
Connect health organisations and enable generation of insights on data that cannot be seen.
While Artificial Intelligence (AI) has been widely used across various industries, it’s usage in health sector has been slow – primarily due to the nature in which AI has worked so far. Until now, the norm is that data needs to be ported to where AI algorithms reside i.e. a centralised approach. However, this approach doesn’t really work in health sector due to data privacy regulations. Some might say anonymise data is always an option but in our experience, it is expensive and doesn’t really guarantee privacy (If you don’t believe us, google ‘Netflix anonymisation’).
So, what if we reverse the entire process to revolutionise healthcare i.e. can algorithms travel to data silos? cHealth aims to achieve exactly that. Using the latest technological innovations in AI (Federated Learning), cHealth allows researchers to deploy their modern algorithms on real data in the wild.
Our team of data scientists have developed and deployed some algorithms which are available for your use from day one. As a macho-algorithm builder, you can configure the system (e.g. disabling model compression, enabling encryption) to develop AI models on productive clinical data.
Converz firmly believes this is a big advantage for the medical organisations, as the organisation receives an algorithm that has been trained on a corpus of data much larger than what it contains. We also ensure the platform is customisable in terms of adding privacy regimes such as Differential Privacy on local data, integrating with your in-house systems and preparing the data pipeline.
Detect up to 15 diseases from Chest imaging scans.
Approximately 23 million X-rays were conducted in the UK alone in 2019. While imaging volumes are slated to increase from 45 million in 2019 to 65 million in 2024, percentage of shortfall of the number of radiologists is slated to increase from 33% to 43% during the same time period. How can hospitals and health organisations brace themselves for this supply demand gap?
Our Chest algorithm not only provides state of the art results, but it also integrates with your in-house systems and gathers feedback to improve. Should you wish to trial this algorithm, please get in touch and we will get back with the credentials to logon. You will need to upload an image and our algorithm will provide an output for you to visualise. Kindly ensure the image does not contain any personal information. If you already have the credentials, please proceed to this page.
Diagnose and treat neurological disorders by calculating the volume of certain parts of the brain.
In 2019, close to 10 million CT and MRI scans were conducted in the UK. The pressure is not only on the system to deliver results quickly and accurately, any delays in the report leads to anxiety in patients. The median wait period for the patient between the request and the actual report for MRI scans is 24 days. How can we improve the patient experience while ensuring the health infrastructure doesn’t collapse?
Artificial Intelligence (AI) technology has provided numerous benefits to organisations of all scales over the last decade. AI’s adoption is no longer an ‘if’ – it is about ‘when’. We are in pilot mode at present and our team of clinical and technical experts are developing an AI model that reads Brain scans and gives details on the volume and state of the disease.
Should you wish to know more about this, please get in touch and we will get back to you.
Our trusted ecosystem to deliver our products to you.
We would love to hear from you, so please drop us a hello and we will get back!
Your message has been send