Xyggy makes it easy and fast for developers to build powerful realtime machine intelligence applications online.
Simply, plugin data of any type - text, image, audio - at one end and get "machine intelligence" on tap at the other end through an interactive API. Data can be unstructured or structured.
This "intelligent data" has multiple uses including 'I am the query' personalization, recommendation system, content discovery, contextual and autonomous discovery, and anomaly detection amongst others.
Xyggy takes care of the complexity of machine learning.
Conventional machine learning methods produce batch applications that have to be regularly re-trained as new data arrives or old data is updated. This means that applications are always using out-of-date data.
Xyggy is realtime from the ground-up. Data can be added and updated in realtime.
Applications built with Xyggy are fully interactive. Queries can be modified on the fly to take advantage of user actions or environment changes. Deliver sophisticated user-experiences with the Xyggy API..
Download the free Xyggy Trial and try Automated Machine Learning in 4 Easy Steps:
1. Assign a unique identifer for each data item.
2. Run the Xyggy Firebox (for deep learning and feature processing).
3. Start the Xyggy Engine.
4. Build with the Xyggy API.
Xyggy has many
If a consumer (or object) is represented by a set of items previously acted on eg. news articles seen, purchases made, url favorites or places visited and so on, then a query with these items will return personalized results. This intuitive method is easy to use and is explained further
Xyggy wants every developer to easily build powerful realtime machine intelligence applications on a fully automated online platform.
Developers do not have to worry about the complexity of machine learning, feature engineering, models, pipelines, algorithms, optimization parameters, cross-validation, endless buzzwords and so on.
Simply, plugin a data source into Xyggy and begin development with the API.
Download the free Xyggy Trial version.
For Windows and Linux.
Most machine learning applications will operate fine on a single 64-bit server but will require lots of memory (ram) as data volumes increase. Since memory is relatively inexpensive this is not a problem. When data is too large for a single server then a distributed architecture (a cluster of computers) becomes necessary.
Xyggy supports both single and distributed architectures and scales effortlessly.
To demonstrate scalability and realtime machine learning,
Email Hello Xyggy, or at the