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Average Ratings 0 Ratings
Description
Clef is a multimodal decision-making model with 27 billion parameters that transforms a given state and a schema of typed inquiries into structured outcomes. This model is capable of interpreting state information presented in various formats, including text, JSON, images, and video, and accordingly generates a probability for each permissible option linked to every question. Supporting a context window of 65,536 tokens along with vision input capabilities, Clef enables developers to analyze both structured application data and visual elements within a unified decision-making process. It accommodates three distinct formats for typed questions: noul, which estimates the likelihood of a proposition being true; choice, which allows for selection among predefined options while providing probabilities for each; and score, which assesses an input against a set of criteria to yield a probability-weighted score. Users can submit anywhere from 1 to 64 questions in a single request, with the corresponding answers returned under the same question identifiers, enhancing the model's efficiency and flexibility. This comprehensive approach ensures that a wide range of applications can leverage Clef's capabilities for diverse decision-making scenarios.
Description
Evaluator assists in making informed decisions by systematically comparing various alternatives against a unified set of criteria. For instance, when choosing a vendor's product or service, factors like features, pricing, and availability are taken into account. Each alternative receives a score based on these criteria, allowing for straightforward comparison among all options. The significance of each criterion can be adjusted through weighting, which modifies its effect on the total evaluation score. This tool also allows for collaborative input, where multiple individuals can contribute their scores, resulting in a consolidated scorecard that reflects the group's collective assessment. The outcomes of this evaluation can be displayed in different formats and compiled into a comprehensive report. Additionally, it is possible to establish a scorecard baseline at any time for auditing purposes. Users can create scorecard templates derived from pre-existing evaluation criteria, facilitating rapid development of new scorecards tailored for evaluating alternative options using the same benchmarks. Furthermore, it is essential to assign a weight to each criterion according to its importance in the decision-making process to ensure balanced evaluations.
API Access
Has API
Yes
API Access
Has API
No
Integrations
JSON
Yes
Markdown
Yes
Mimasa AI
No
Python
Yes
TypeScript
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
Yes
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Cloudflare
Founded
2009
Country
United States
Website
developers.cloudflare.com/workers-ai/models/clef/
Vendor Details
Company Name
Midrig
Country
United Kingdom
Website
midrig.com/evaluator/
Product Features
Product Features
Decision Support
Application Development
No
Budgeting & Forecasting
No
Data Analysis
Yes
Decision Tree Analysis
No
Monte Carlo Simulation
No
Performance Metrics
No
Rules-Based Workflow
No
Sensitivity Analysis
No
Thematic Mapping
No
Version Control
No