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What is Scale GenAI Platform?

Create, assess, and enhance Generative AI applications that reveal the potential within your data. With our top-tier machine learning expertise, innovative testing and evaluation framework, and sophisticated retrieval augmented-generation (RAG) systems, we enable you to fine-tune large language model performance tailored to your specific industry requirements. Our comprehensive solution oversees the complete machine learning lifecycle, merging advanced technology with exceptional operational practices to assist teams in producing superior datasets, as the quality of data directly influences the efficacy of AI solutions. By prioritizing data quality, we empower organizations to harness AI's full capabilities and drive impactful results.

What is Evidently AI?

A comprehensive open-source platform designed for monitoring machine learning models provides extensive observability capabilities. This platform empowers users to assess, test, and manage models throughout their lifecycle, from validation to deployment. It is tailored to accommodate various data types, including tabular data, natural language processing, and large language models, appealing to both data scientists and ML engineers. With all essential tools for ensuring the dependable functioning of ML systems in production settings, it allows for an initial focus on simple ad hoc evaluations, which can later evolve into a full-scale monitoring setup. All features are seamlessly integrated within a single platform, boasting a unified API and consistent metrics. Usability, aesthetics, and easy sharing of insights are central priorities in its design. Users gain valuable insights into data quality and model performance, simplifying exploration and troubleshooting processes. Installation is quick, requiring just a minute, which facilitates immediate testing before deployment, validation in real-time environments, and checks with every model update. The platform also streamlines the setup process by automatically generating test scenarios derived from a reference dataset, relieving users of manual configuration burdens. It allows users to monitor every aspect of their data, models, and testing results. By proactively detecting and resolving issues with models in production, it guarantees sustained high performance and encourages continuous improvement. Furthermore, the tool's adaptability makes it ideal for teams of any scale, promoting collaborative efforts to uphold the quality of ML systems. This ensures that regardless of the team's size, they can efficiently manage and maintain their machine learning operations.

Media

Media

Integrations Supported

Amazon S3
Azure Blob Storage
Azure Marketplace
Claude
Claude Duet
Claude for Legal
Coral
Diffgram Data Labeling
Google Cloud Storage
Google Docs
OpenAI
Pilot
Unremot

Integrations Supported

ZenML

API Availability

Has API

API Availability

Pricing Information

Pricing not provided
Free Trial Offered?

Pricing Information

$500 per month
Free Version

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

24 Hour Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub

Company Facts

Organization Name

Scale AI

Date Founded

2016

Company Location

United States

Company Website

scale.com

Company Facts

Organization Name

Evidently AI

Date Founded

2020

Company Location

United States

Company Website

www.evidentlyai.com

Categories and Features

AI Development

Not specified

Artificial Intelligence

For Healthcare
For Sales
For eCommerce
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation

Data Annotation

Not specified

Generative AI

Not specified

Machine Learning

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

Natural Language Processing

Co-Reference Resolution
In-Database Text Analytics
Named Entity Recognition
Natural Language Generation (NLG)
Parsing
Part-of-Speech Tagging
Sentence Segmentation

Categories and Features

AI Development

Not specified

AI Observability

Not specified

Data Quality

Not specified

Machine Learning

Not specified

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