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ease
features
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support

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Description

Launch top-notch LLM applications swiftly while maintaining rigorous testing standards. You should never feel constrained by the intricate and often subjective aspects of LLM interactions. Generative AI often yields subjective outcomes, and determining the quality of generated content frequently necessitates the expertise of a subject matter professional. If you're developing an LLM application, you're likely aware of the myriad constraints and edge cases that must be managed before a successful release. Issues such as hallucinations, inaccurate responses, biases, policy deviations, and potentially harmful content must all be identified, investigated, and addressed both prior to and following the launch of your application. Deepchecks offers a solution that automates the assessment process, allowing you to obtain "estimated annotations" that only require your intervention when absolutely necessary. With over 1000 companies utilizing our platform and integration into more than 300 open-source projects, our core LLM product is both extensively validated and reliable. You can efficiently validate machine learning models and datasets with minimal effort during both research and production stages, streamlining your workflow and improving overall efficiency. This ensures that you can focus on innovation without sacrificing quality or safety.

Description

Symflower revolutionizes the software development landscape by merging static, dynamic, and symbolic analyses with Large Language Models (LLMs). This innovative fusion capitalizes on the accuracy of deterministic analyses while harnessing the imaginative capabilities of LLMs, leading to enhanced quality and expedited software creation. The platform plays a crucial role in determining the most appropriate LLM for particular projects by rigorously assessing various models against practical scenarios, which helps ensure they fit specific environments, workflows, and needs. To tackle prevalent challenges associated with LLMs, Symflower employs automatic pre-and post-processing techniques that bolster code quality and enhance functionality. By supplying relevant context through Retrieval-Augmented Generation (RAG), it minimizes the risk of hallucinations and boosts the overall effectiveness of LLMs. Ongoing benchmarking guarantees that different use cases remain robust and aligned with the most recent models. Furthermore, Symflower streamlines both fine-tuning and the curation of training data, providing comprehensive reports that detail these processes. This thorough approach empowers developers to make informed decisions and enhances overall productivity in software projects.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Android Studio
Claude
Claude Haiku 3
Codestral Mamba
Cohere
JUnit
Le Chat
Llama 3
Meta AI
Ministral 3B
Ministral 8B
Mistral AI
Mistral Large
Mistral NeMo
Mistral Small
Mixtral 8x22B
OpenAI
Perplexity
Pixtral Large
Python

Integrations

Android Studio
Claude
Claude Haiku 3
Codestral Mamba
Cohere
JUnit
Le Chat
Llama 3
Meta AI
Ministral 3B
Ministral 8B
Mistral AI
Mistral Large
Mistral NeMo
Mistral Small
Mixtral 8x22B
OpenAI
Perplexity
Pixtral Large
Python

Pricing Details

$1,000 per month
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Deepchecks

Founded

2019

Country

United States

Website

deepchecks.com

Vendor Details

Company Name

Symflower

Founded

2018

Country

Austria

Website

symflower.com

Product Features

Product 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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