Opportunity matcher

Trust Layer | by Assenteo

By:Law School 2.0

Issued: 2025-09-17

This certificate summarizes the information Law School 2.0 has provided about Opportunity matcher and its data usage.

To learn whether Law School 2.0 meets additional AI governance standards, contact us here.

Opportunity matcher

Product Name

Law School 2.0

Company

Sep 2025

Certificate Issued

Product Overview

Purposes & Use Cases

No purposes defined

AI Model

Single model: Open AI, GPT-4

Certificate issued: 2025-09-17

Last updated: 2025-09-17

Purpose Analysis

No purposes defined for this product.

Trust & Safety

Answers to key questions about data usage, privacy, and safety practices.

What can users set preferences on?

Selected practices:

To train and improve models

Available options (for reference):

To train and improve modelsAny user can opt outOpt out only possible for enterprises

About the Company

This product is offered by Law School 2.0. View their full certificate for complete company information.

Law School 2.0

LegalTech Education

3,000+

Product Focus

To provide theoretical training and practical opportunities for legal professionals at all career stages to innovate within law, develop new skills in legal innovation, and improve the profession through hands-on experiences and community engagement.

Target Users

Lawyers

View full company certificate

How is customer data used to improve your product?

Selected practices:

Customer data is not used to train our models

All customer data is used to train our models

Available options (for reference):

Customer data is not used to train our modelsAll customer data is used to train our models We provide a tier where customer data is not used to train our models

How would you currently explain an unexpected or harmful model output?

Selected practices:

We log prompts and responses so we can review input vs. output

Available options (for reference):

We log prompts and responses so we can review input vs. outputWe analyze patterns in the model’s responses across similar casesWe apply post-processing rules or filters to detect or block unsafe outputsWe involve a human in the loop for review or escalationWe use structured or templated prompting to reduce unpredictability

Opportunity matcher

Product Overview

Purposes & Use Cases

AI Model

Purpose Analysis

Trust & Safety

What can users set preferences on?

About the Company

Law School 2.0

Product Focus

Target Users

Why do you share collected data with third parties?

How is customer data used to improve your product?

How would you currently explain an unexpected or harmful model output?

Summary