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What is Syntronik?

Syntronik is a cutting-edge virtual synthesizer that elevates sound quality and versatility through advanced sampling techniques and a groundbreaking hybrid synthesis engine that combines sampling with modeling. It boasts a selection of 17 exceptional synthesizers, available for purchase as a complete set or individually, and provides more than 2,000 preset sounds that cover a wide spectrum, including 38 iconic and rare vintage synths that have been meticulously multi-sampled. The synthesis engine of Syntronik goes beyond traditional sampling methods, featuring a newly designed analog modeled filter section that showcases IK's expertise in virtual circuit modeling. Furthermore, the exclusive DRIFTâ„¢ technology is employed to realistically replicate the behavior of oscillators from genuine hardware synthesizers. This innovative platform is also equipped with an extraordinary effects section and advanced functionalities like 4-part Multis, splits, and arpeggiators, establishing Syntronik as the ultimate source of creative inspiration for musicians and producers alike. With its extensive array of tools, Syntronik encourages users to delve deep into their creativity, enabling them to produce sounds and compositions that were once thought to be unattainable. The platform continues to redefine possibilities in music production by merging traditional sounds with modern technology.

What is 3LC?

Illuminate the opaque processes of your models by integrating 3LC, enabling the essential insights required for swift and impactful changes. By removing uncertainty from the training phase, you can expedite the iteration process significantly. Capture metrics for each individual sample and display them conveniently in your web interface for easy analysis. Scrutinize your training workflow to detect and rectify issues within your dataset effectively. Engage in interactive debugging guided by your model, facilitating data enhancement in a streamlined manner. Uncover both significant and ineffective samples, allowing you to recognize which features yield positive results and where the model struggles. Improve your model using a variety of approaches by fine-tuning the weight of your data accordingly. Implement precise modifications, whether to single samples or in bulk, while maintaining a detailed log of all adjustments, enabling effortless reversion to any previous version. Go beyond standard experiment tracking by organizing metrics based on individual sample characteristics instead of solely by epoch, revealing intricate patterns that may otherwise go unnoticed. Ensure that each training session is meticulously associated with a specific dataset version, which guarantees complete reproducibility throughout the process. With these advanced tools at your fingertips, the journey of refining your models transforms into a more insightful and finely tuned endeavor, ultimately leading to better performance and understanding of your systems. Additionally, this approach empowers you to foster a more data-driven culture within your team, promoting collaborative exploration and innovation.

Media

Media

Integrations Supported

Amazon Web Services (AWS)
Apache Arrow
Apache Parquet
Google Cloud Platform
Google Colab
Hugging Face
Jupyter Notebook
Microsoft Azure
NumPy
PyTorch
Python
pandas

Integrations Supported

Amazon Web Services (AWS)
Apache Arrow
Apache Parquet
Google Cloud Platform
Google Colab
Hugging Face
Jupyter Notebook
Microsoft Azure
NumPy
PyTorch
Python
pandas

API Availability

Has API

API Availability

Has API

Pricing Information

$299.99 one-time payment
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Ik Multimedia

Date Founded

1996

Company Location

United States

Company Website

www.ikmultimedia.com/products/syntronik/

Company Facts

Organization Name

3LC

Company Website

3lc.ai/

Categories and Features

Categories and Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

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