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What is Wolfram System Modeler?

With a user-friendly drag-and-drop feature that encompasses a wide selection of both pre-existing and expandable modeling libraries, you can design complex, multidomain models that accurately depict your entire system. The incorporation of the Wolfram Language enhances this process by offering a thorough environment for the evaluation, understanding, and swift iteration of system designs, which ultimately leads to valuable insights, innovative solutions, and concrete results. In practice, machines and systems rarely conform to a single physical domain; models often consist of various interconnected elements from multiple domains that mirror real-world scenarios. This allows for immediate exploration, as you can access all component values in your model with a simple click. You can investigate specific areas of interest and choose from an array of built-in plotting options, all through an intuitive point-and-click interface. Moreover, you have the ability to perform both symbolic and numerical analyses utilizing the complete set of model equations and simulation results. This dynamic integration maximizes the advantages of the Wolfram Language in your modeling endeavors, positioning it as an essential asset for engineers and designers. Additionally, the capability to fluidly switch between different domains within your model cultivates a more profound comprehension of intricate systems, enabling users to better anticipate potential issues and optimize designs accordingly.

What is Symflower?

Symflower transforms the realm of software development by integrating static, dynamic, and symbolic analyses with Large Language Models (LLMs). This groundbreaking combination leverages the precision of deterministic analyses alongside the creative potential of LLMs, resulting in improved quality and faster software development. The platform is pivotal in selecting the most fitting LLM for specific projects by meticulously evaluating various models against real-world applications, ensuring they are suitable for distinct environments, workflows, and requirements. To address common issues linked to LLMs, Symflower utilizes automated pre-and post-processing strategies that improve code quality and functionality. By providing pertinent context through Retrieval-Augmented Generation (RAG), it reduces the likelihood of hallucinations and enhances the overall performance of LLMs. Continuous benchmarking ensures that diverse use cases remain effective and in sync with the latest models. In addition, Symflower simplifies the processes of fine-tuning and training data curation, delivering detailed reports that outline these methodologies. This comprehensive strategy not only equips developers with the knowledge needed to make well-informed choices but also significantly boosts productivity in software projects, creating a more efficient development environment.

Media

Media

Integrations Supported

Claude
Codestral
Command R
Command R+
DeepSeek
GPT-4
GPT-4 Turbo
Gemini Flash
JUnit
Llama 3
Ministral 3B
Mistral 7B
Mistral AI
Mistral Large
Mixtral 8x22B
Mixtral 8x7B
OpenAI
Perplexity
Qwen
Visual Studio Code

Integrations Supported

Claude
Codestral
Command R
Command R+
DeepSeek
GPT-4
GPT-4 Turbo
Gemini Flash
JUnit
Llama 3
Ministral 3B
Mistral 7B
Mistral AI
Mistral Large
Mixtral 8x22B
Mixtral 8x7B
OpenAI
Perplexity
Qwen
Visual Studio Code

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
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

Wolfram

Date Founded

1987

Company Location

United States

Company Website

www.wolfram.com/system-modeler/

Company Facts

Organization Name

Symflower

Date Founded

2018

Company Location

Austria

Company Website

symflower.com

Categories and Features

Categories and Features

Software Testing

Automated Testing
Black-Box Testing
Dynamic Testing
Issue Tracking
Manual Testing
Quality Assurance Planning
Reporting / Analytics
Static Testing
Test Case Management
Variable Testing Methods
White-Box Testing

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