Advanced machine learning
We solve hard problems using advanced machine learning techniques.
To do this, we're building the Nuroko Toolkit - a flexible suite of machine learning algorithms that can be applied to a broad range of situations.
The Nuroko Toolkit unlocks value from any source of data, and as such can be applied in virtually any area. Here are some examples of the kind of real problems we can help you to solve:
- Internet of Things: How do we integrate and extract meaningful patterns from thousands of interconnected sensor data streams?
- Healthcare: Based on imperfect medical record information, how do we identify which patients would benefit most from a specific treatment programme?
- Insurance: Given our current knowledge about a specific risk, what is the expected value of claims?
- Fraud detection: Can we estimate in realtime if a transaction is likely to be fraudulent, and if so refer it to a dedicated team for further scrutiny?
- Process Automation: How is a process behaving, and how do we predict it will behave in the next 24 hours so that we can manage downstream impact?
- B2C Marketing: What will an individual customer be eager to buy next, based on past behaviour data?
If you think you could benefit from this technology, or if you are interested in partnering with us to deliver advanced machine learning solutions, contact us at: firstname.lastname@example.org.
- General purpose
The Nuroko toolkit is a 100% flexible solution.
- Handle any kind of data: text, images, numbers, structured and unstructured records.
- Avoid the need for expensive customisation. Many problems can be solved with no code changes.
- Incorporate new data feeds easily.
Advanced machine learning algorithms for pattern recognition and prediction are at the heart of the Nuroko Toolkit.
- Automatically extract relevant data from irrelevant noise.
- Detect "deep" patterns in data - unaccessible using other methods.
- Maximise the value from more accurate predictions
Everything in the Nuroko toolkit is suitable for online, realtime usage (in addition to traditional batch-based processing)
- Train models in realtime, so you can respond to dynamically changing environments.
- Run models in realtime, so you can react instantaneously to new data.
- Embed models easily in online and mobile applications for realtime usage.
We've built the Nuroko Toolkit to be completely ready for the challenges of Big Data
- Distribute model training and execution in cloud-based environments.
- Handle datasets of arbitrary size.
- Integrate with other Big Data applications.
The Nuroko approach is designed for real-world usage.
- Models can be deployed and integrated as part of your application environment.
- Local API for direct use in JVM applications - run from Java, Clojure or Scala.
- Option to deploy as a scalable web service for heterogeneous clients.