Entrepreneurship Education vertical

Founder education built on the CRIAR® methodology.

A proprietary entrepreneurship pedagogy developed by Adriano Salvador since 2005, refined over two decades of applied practice, and operationalized into platform modules across founder cohorts.

Curriculum tracks

Structured pathways, expert-guided.

Every track is operationalized under the founder's methodological supervision and versioned quarterly to reflect updated research and applied outcomes.

Ideation Sprint

Opportunity discovery, problem framing, and early hypothesis design for first-time founders.

Business Model Design

Canvas iteration, unit-economics modeling, and segmentation under expert guidance.

Validation Lab

Customer interviews, problem-solution fit instrumentation, and early-signal frameworks.

Early Customers

Go-to-market playbooks, pricing experimentation, and channel selection for SMB founders.

Funding Basics

Bootstrapping, SBA pathways, and capital-stack literacy for non-VC founders.

Founder Mentor Matching

Cohort participants are matched with experienced operators for periodic methodology checkpoints.

Founder's Curriculum Note

The CRIAR® framework emerged from direct classroom practice across multiple basic-education institutions in Brazil and was refined across two decades of applied work. Translating that pedagogy into an American SMB founder cohort requires continuous methodological supervision — the model travels, and the quality assurance travels with it.

— Adriano Salvador, Founder & CEO

Outcomes

By the numbers.

These outcomes were produced by the educational-management engagements that informed the methodology now operating in the platform.

2,000+

Learners trained under the CRIAR® methodology to date

Multi-school

Original deployment across multiple basic-education institutions in Brazil

55-member

Utah entrepreneurs community — founder serves as elected president, applying the CRIAR® methodology operationalized in the platform

Two decades

Continuous methodology iteration and applied refinement