ABOUT US

A model integration-first AI platform,
that will enable automation, recognize hidden patterns and capture key insights.

Jiva.ai empowers organizations with the tools and computation capacity to create Machine Learning models so that they can make the most out of their data.

Predict
Predict
outcomes and recognize hidden patterns
Solve
Solve
healthcare problems
& improve efficiencies and human health outcomes.
Enhance
Enhance
existing capabilities by arming them with AI-driven custom software

FOCUS

Machine Learning

Healthcare systems must operate under the strain of ever-increasing patient demand whilst maintaining an acceptable level of care.

AI and machine learning can help reduce that burden by saving both time and money in diagnosis, automation and proactive prediction.

Jiva.ai can provide quantifiable value to the healthcare sector

Smart diagnosis
Smart diagnosis
Clinical trial backed solutions to enhance and aid the current diagnostic pathway
Proactive detection
Proactive detection
Integration of Jiva solutions into hospital systems, such as PACS, for frictionless and automated processes
Live Monitoring
Live Monitoring
Realtime speed of execution, triggering fast alerting for medical staff
Custom solutions
Custom solutions
Have a specific use case?
Let’s talk. Jiva.ai is extremely versatile and can be shaped to specific requirements

We currently work with the following core healthcare and life sciences segments

Health Services Providers

Health Services Providers

Pharma Life Sciences

Pharma Life Sciences

Consumer Health

Consumer Health

Medical Insurance

Medical Insurance

SOLUTION

Jiva.ai

Jiva.ai is deployed via a simple 3 step process
ABOUT US
1
Data aggregation
to extract relevant
information in real-time for
our algos to analyse
2
Recognition
of patterns and
anti-patterns
3
Adaptive learning
Jiva.ai gets smarter over time
Here are a few use-cases that Jiva.ai is currently deployed to solve or in consultation
  • USE CASE 1
  • USE CASE 2
  • USE CASE 3
  • USE CASE 4
  • USE CASE 5
MRI Imaging Analytics for Prostate Cancer

Prostate cancer is set to become the most common cancer in men with approximately 50,000 new cases every year. Subjectivity in diagnosis is a known issue with sensitivity recorded as low as 57%. A high time and economic cost of post-biopsy complications means that radiologists are under increasing pressure to improve efficiency.

Jiva.ai is set to become the first AI-based solution trained on a unique set of labelled T3 MRI scans to identify tumours that would otherwise be missed. The trained kernel is due to go to clinical trial in late 2019/early 2020.

Live Analytics

A model integration-first AI platform,<br /> that will enable automation, recognize hidden patterns and capture key insights.Jiva.ai empowers organizations with the tools and computation capacity to create Machine Learning models so that they can make the most out of their data.

Palliative Care

A model integration-first AI platform,<br /> that will enable automation, recognize hidden patterns and capture key insights.Jiva.ai empowers organizations with the tools and computation capacity to create Machine Learning models so that they can make the most out of their data.

Preventative Medicine

A model integration-first AI platform,<br /> that will enable automation, recognize hidden patterns and capture key insights.Jiva.ai empowers organizations with the tools and computation capacity to create Machine Learning models so that they can make the most out of their data.

Falls Pathway

A model integration-first AI platform,<br /> that will enable automation, recognize hidden patterns and capture key insights.Jiva.ai empowers organizations with the tools and computation capacity to create Machine Learning models so that they can make the most out of their data.

TECHNOLOGY

Under the Hood

The algorithm that powers Jiva.ai is a class of deep learning, similar to TensorFlow, but with a different flow of execution. The main difference is that Jiva.ai incorporates real-world semantics into the model. This allows the ability to not only modify the model iteratively, but also integrate different models together.

For example, you may want to integrate kernels (predictors) between the following markers:

(a) Genetic markers for diabetes
(b) Genetic markers for heart disease
(c) Socio-demographic factors

age, income, house prices, environmental factors, etc

These models can be learned separately, and integrated later, this would highlight any co-factors or anomalies worth investigating. This also allows us to have an AI algorithm more suitable for real world problems. The idea is to improve your machine learning capability over time. As disparate kernels get added Jiva.ai will evolve its general artificial intelligence.

WHO IS JIVA?

Our team with Big Ideas

Dr Chetan Kaher

Dr Chetan Kaher

Business & Growth

Chetan has a doctorate in dentistry and a BSc in Immunology & Oncology with publications in developing anti-cancer proteins. He is currently on the NHS Clinical Entrepreneurship Scheme, to implement Jiva.ai into healthcare systems.

Dr Manish Patel

Dr Manish Patel

Technical Lead

Manish has a doctorate in mathematical modelling with an emphasis on dealing with large, complex datasets. He is the technical architect of Jiva.ai, a new machine learning algorithm that will form the basis of a new breed of AIs.

Sarah D’Souza

Sarah D’Souza

CIO & Operations

Sarah is an experienced management and banking professional with a background in law. As well as being a successful entrepreneur, Sarah joins the team taking control of project  management, operations and all things legal & data security.

Dr Andrew J. Thompson

Dr Andrew J. Thompson

Funding Strategy

Andy is heads funding strategy and is a professional grant writer. He has extensive experience developing business, R&D and fundraising strategy, and preparing and implementing winning business cases.

PARTNERS

Our strategic partners

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