gliff.ai offers secure, easy-to-use, low-code/no-code MLOps tools to make developing an imaging AI as simple as possible.
Our software platform is specifically designed for teams who are developing AI solutions for healthcare, biomedicine and pharmaceuticals – but our MLOps tools are available to anyone in any industry.
Artificial Intelligence (AI) will revolutionise healthcare, improve outcomes for patients and support medical practitioners around the world. To realise these benefits, the process for developing trustworthy AI needs to be easier and more open.
End-to-end encryption to keep data secure
Enables team members to work together
Open-source and built-in audit trails for transparency
Saves time and money in AI development
Contact us to discover how gliff.ai can help your current or future AI project by streamlining development processes, saving you time and money.
Privacy Preserving Machine Learning
Your data will always be your data.
gliff.ai does not aggregate or monetise users’ data – and going further than other platforms, gliff.ai provides end-to-end encryption to ensure that highly sensitive and commercially valuable data are always secure.
In healthcare, data used for AI development may contain personally identifiable patient information or patients’ medical images like OCT, MRI and CT scans. Therefore, preserving patient confidentiality has to be central to any platform used for processing data. That’s why privacy and security are at the heart of what gliff.ai does.
Discover the other benefits gliff.ai provides on our Software page.
MLOps tools that save time and money:
5 years and £2 million can be saved by not building a data platform in-house.
At gliff.ai, we develop MLOps tools that streamline the data preparation stages in AI development, so that we can help our users save time and money, and ultimately accelerate processes so that more trustworthy AI solutions can reach the clinicians and patients.
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What are MLOps tools?
Machine learning is a sub-field of AI which focuses on data and algorithms so that models can learn to mimic the decisions of expert humans. For example, a team of oncology experts may use machine learning to develop an AI that can detect tumours from patient MRI scans, just like a radiologist would do in a hospital.
Machine Learning Operations (MLOps) relates to the practices for developing, deploying and maintaining machine learning models.
MLOps tools are software tools designed to help you implement Machine Learning Operations practices.
