LANFINITAS AI Social Impact Metrics & Tracking Framework UN SDG Alignment Report

EXECUTIVE SUMMARY

Lanfinitas AI creates measurable social impact by democratizing pattern-making expertise, traditionally requiring 5-10 years of training. Our AI-powered platform reduces barriers to entry by 95%, enabling independent designers, Global South manufacturers, people with disabilities, and small brands to access professional-grade tools at €20/month (vs. €3,000-10,000 traditional software). We track impact across three dimensions: Access & Equity, Economic Empowerment, and Skills & Education.

UN SUSTAINABLE DEVELOPMENT GOALS ALIGNMENT

SDG Target Our Contribution Measurement Metric

SDG 4:

Quality

Education

4.4: Increase technical skills

4.5: Equal access for vulnerable

Fashion academy partnerships,

free educational tier,

disability-accessible design

Students reached,

skills acquired,

accessibility usage

SDG 5:

Gender

Equality

5.5: Women in leadership,

5.b: Technology for empowerment

Female founder/CEO,

technology democratization

Female user %,

leadership diversity

SDG 8:

Decent Work

8.2: Economic productivity,

8.3: Entrepreneurship,

8.5: Employment for disabled

€95K-132K savings/client,

artisan employment,

accessible work tools

Jobs created,

economic impact,

disability employment

SDG 9:

Industry

Innovation

9.3: Access to technology Affordable SaaS (€20/mo),

cloud-based accessibility

Geographic reach,

pricing accessibility

SDG 10:

Reduced

Inequalities

10.2: Economic inclusion,

10.3: Equal opportunity

Global South access,

no geographic barriers,

disability inclusion

User diversity,

regional distribution,

accessibility adoption

SDG 12:

Responsible

Consumption

12.2: Sustainable resource use Zero-waste digital workflow,

circular economy model

Waste reduction,

circular adoption

THREE DIMENSIONS OF SOCIAL IMPACT

Dimension Problem Addressed Our Solution Target Beneficiaries

1. ACCESS &

EQUITY

Pattern-making requires 5-10

years training; creates elite

gatekeeping; physical barriers

for disabled designers

AI reduces to 30-second

generation; 95% cost

reduction; accessible

digital interface

500K independent designers;

Global South manufacturers;

people with disabilities

2. ECONOMIC

EMPOWERMENT

Small brands cannot afford

€3K-10K CAD licenses;

sampling costs prohibitive

€20/month entry price;

€95K-132K annual savings

per client

SME fashion brands;

freelance designers;

emerging market producers

3. SKILLS &

EDUCATION

Shortage of skilled patternmakers;

training institutions

lack digital tools

Free educational tier;

fashion academy partnerships;

open-source resources

5,000+ fashion schools

globally; students in

developing countries

KEY SOCIAL IMPACT METRICS (Baseline & Projections)

Metric Current (Nov 2025) 2026 Target 2028 Target Measurement Method

Users reached 50 (waitlist) 10,000 200,000 Platform registrations

Paying customers 0 (pre-revenue) 500 10,000 Active subscriptions

Cost accessibility €20/mo (95% lower) Maintained Maintained Pricing vs. alternatives

Economic impact/client Projected: €95K-132K Validated Scaled Annual savings surveys

Educational partnerships 0 (discussions: 3) 5 academies 50 academies Partnership agreements

Global South users N/A 20% of base 35% of base Geographic analytics

Female users N/A 60% 55% Self-reported demographics

Accessibility adoption N/A 5% usage 10% usage Assistive tech analytics

Jobs created (circular) 0 (pilot: 15) 100 artisans 1,000 artisans Employment records

STAKEHOLDER IMPACT ANALYSIS

Who Benefits & How

STAKEHOLDER GROUP 1: Independent Designers

Population: ~500,000 globally (emerging/freelance designers)

Current Barriers:

• Cannot afford €3,000-10,000 CAD software licenses

• Lack 5-10 years formal pattern-making training

• Must outsource pattern development (€500-2,000 per collection)

• Geographic isolation (no access to skilled pattern-makers)

How Lanfinitas AI Helps:

3 95% cost reduction: €20/month vs. €3,000-10,000 traditional software

3 Instant expertise: AI generates production-ready patterns in 30 seconds

3 Creative autonomy: No dependence on external pattern-makers

3 Faster iteration: Test 10+ design variations in time previously needed for 1

Validated Impact (n=8 designer interviews):

• 100% confirmed willingness to pay €20-50/month

• Average time savings: 15-20 hours per collection

• Reported barrier reduction: "Makes professional design accessible for the first time"

2026 Target: 300 independent designer subscribers (60% of paying customer base)

STAKEHOLDER GROUP 2: People with Disabilities

Population: ~61 million people with disabilities in fashion/creative industries globally

Current Barriers:

• Traditional pattern-making requires significant manual dexterity (physical disability barrier)

• CAD software interfaces not optimized for screen readers or assistive technologies

• Physical access to fashion education/ateliers limited

• Employment discrimination in traditional fashion manufacturing

How Lanfinitas AI Enables Disability Inclusion:

3 No manual dexterity required: AI generates patterns from 3D designs, eliminating hand-drafting

3 Voice interface compatible: Platform designed for screen reader accessibility

3 Remote work enabled: Cloud-based system eliminates need for physical studio access

3 Cognitive load reduction: AI handles technical calculations, designer focuses on creativity

3 Economic independence: Low-cost entry enables self-employment opportunities

Accessibility Features (Planned Q2 2026):

• WCAG 2.1 Level AA compliance (Web Content Accessibility Guidelines)

• Screen reader optimization (JAWS, NVDA, VoiceOver compatible)

• Keyboard navigation (no mouse required)

• High-contrast mode for visual impairment

• Voice command integration (planned 2027)

Impact Potential:

Fashion design becomes accessible to disabled creators who were previously excluded by physical requirements of

traditional pattern-making. This aligns with SDG 8.5 (full employment for persons with disabilities) and SDG 10

(reduced inequalities).

2026 Target: 5% of user base includes people with disabilities (500 users)

STAKEHOLDER GROUP 3: Small-Medium Fashion Brands

Population: ~100,000 companies globally (10-500 SKUs/year)

Current Challenges:

• High sampling costs: €36,000-48,000 annually for 200 SKUs

• Long lead times: 6-12 months design-to-production

• Cannot compete with fast fashion speed

How Lanfinitas AI Helps:

3 Economic viability: €95,000-132,000 annual savings enables sustainable business model

3 Speed to market: 70% faster pattern development

3 ESG compliance: 98.6% CO2 reduction supports sustainability reporting

2026 Target: 100 SME brand subscribers (20% of customer base)

STAKEHOLDER GROUP 4: Global South Manufacturers

How Lanfinitas AI Enables:

3 Geographic equity: Cloud-based access removes location barriers

3 Affordable expertise: €50-500/month vs. €10,000+ consulting fees

3 Language-agnostic: Visual interface, multilingual support (planned 2027)

Founder Connection: China-based operations with European training bridges cultural/technical gap.

2026 Target: 20% of user base from Global South (2,000 users)

EDUCATION & EMPLOYMENT IMPACT

EDUCATIONAL PARTNERSHIPS & SKILLS DEVELOPMENT

Problem Statement:

Fashion education institutions (5,000+ schools globally) face challenges:

• Traditional CAD software costs €50,000-200,000 for 20-seat lab licenses

• Pattern-making curriculum requires expert instructors (scarce talent)

• Students graduate without industry-standard digital skills

• Developing countries lack access to expensive software

Lanfinitas AI Educational Program (Launching Q2 2026):

Free Educational Tier:

3 Unlimited access for verified students & educators

3 Collaborative classroom features

3 Curriculum integration guides

3 Student portfolio hosting

Fashion Academy Partnerships:

• Current discussions: 3 institutions (domestic & international)

• 2026 target: 5 formal partnerships

• 2028 target: 50 academies, reaching 10,000+ students annually

Open-Source Contribution:

• Frontend code: Apache 2.0 license (Nov 2025)

• Technical documentation: Publicly available

• Research collaboration: Industry-academia partnerships planned (domestic & international institutions)

EMPLOYMENT IMPACT: Direct & Indirect Job Creation

Job Category Current 2026 2028 Description

Direct Employment (Lanfinitas AI)

Company team 1 (founder) 4.5 FTE 14 FTE ML engineers, developers, operations

Indirect Employment (Client-Side)

Designers enabled 0 500 10,000 Independent designers accessing tools

SME brand employees 0 2,500 50,000 Brands using platform (avg 5 employees)

Artisan Employment (Circular Economy Model)

Satellite hub artisans 0 (pilot: 15) 100 1,000 Upcycling/redesign artisans

Hub coordinators 0 10 50 Local hub management

Total Ecosystem Employment 1 <b>3,114</b> <b>61,064</b> Combined direct + indirect + artisan

Note on Circular Economy Model: Our pilot circular fashion project (HarmonAIze, Solar Impulse Efficient Solution

Label 2025) uses AI to identify upcycling opportunities in excess inventory, then coordinates distributed "satellite hubs"

of local artisans to execute redesign. This preserves craft livelihoods while scaling circular economy. The model

demonstrates how Lanfinitas AI technology enables social impact beyond direct platform usage.

GENDER EQUITY & FEMALE LEADERSHIP

Female Founder in Male-Dominated Fields:

• AI/ML startups: Only 12% have female founders (PitchBook 2024)

• Fashion manufacturing: Pattern-making historically male-dominated profession in Europe/Asia

• Technical leadership: Fashion tech companies: 18% female technical founders

Our Commitment to Gender Equity:

3 Female founder/CEO (Lu Min) with 20+ years fashion expertise

3 Hiring targets: 50%+ female technical team by 2027

3 Pricing accessibility benefits women disproportionately (70% of fashion designers are women, but face greater

barriers to capital)

3 Educational partnerships prioritize institutions serving underrepresented students

Expected User Demographics (2026):

• Female users: 60-70% (fashion industry demographic)

• Users from developing countries: 20%

• First-time fashion entrepreneurs: 40%

Visibility & Representation:

VivaTech Female Founder recognition amplifies visibility of women in AI × Manufacturing intersection, demonstrating

technical leadership viability in traditionally male spaces.

MEASUREMENT METHODOLOGY & VALIDATION

SOCIAL IMPACT TRACKING FRAMEWORK

Impact Area Key Metrics Data Collection Method Frequency Public Reporting

Access &

Equity

• Users by geography

• Cost vs. alternatives

• Disability accessibility

Platform analytics

Pricing benchmarking

Assistive tech tracking

Monthly

Quarterly

Monthly

Annual report

Economic

Empowerment

• Client savings

• SME viability rate

• Revenue per designer

Economic impact surveys

Retention tracking

Case studies

Quarterly

Monthly

Annual

Annual +

case studies

Skills &

Education

• Educational partnerships

• Students reached

• Skill acquisition

Partnership agreements

Institution reporting

Learning assessments

Quarterly

Semester

Annual

Annual report

Employment • Jobs created

• Artisan income

• Gender diversity

Employment records

Hub coordinator reports

Self-reported data

Monthly

Quarterly

Annual report

Diversity &

Inclusion

• Female users %

• Global South %

• Disability users %

Optional user surveys

Geographic analytics

Platform accessibility

Quarterly

Monthly

Annual report

B IMPACT ASSESSMENT FRAMEWORK (Planned)

Target: B Corporation Certification by 2028

We are structuring our social impact tracking to align with B Lab's Impact Assessment framework, positioning for B

Corp certification once revenue exceeds €500K (prerequisite).

B Impact Assessment Areas (5 categories):

1. Governance (Current Score Estimate: 15-20 / 20 points):

3 Mission lock (sustainability mission in founding documents)

3 Stakeholder governance (customer advisory board planned 2027)

3 Transparency (open-source code, public impact reporting)

2. Workers (Target Score: 25-30 / 40 points by 2027):

3 Fair compensation (market rate + equity)

3 Gender diversity targets (50%+ female technical team)

3 Remote-first flexibility

3 Professional development budget

3. Community (Current Estimate: 35-45 / 40 points):

3 Supplier diversity (Global South partnerships)

3 Charitable giving (5% profit donation commitment)

3 Job creation (artisan employment via circular model)

3 Civic engagement & advocacy

4. Environment (Current: 30-35 / 40 points):

3 Environmental management system (LCA tracking)

3 Pollution/waste reduction (98.6% CO2 reduction validated)

3 Renewable energy (>80% via Google Cloud)

3 Circular inputs (digital-first eliminates material waste)

5. Customers (Target: 20-25 / 20 points):

3 Product mission: democratization + sustainability + disability inclusion (triple benefit)

3 Underserved customers (Global South, independent designers, people with disabilities)

3 Customer stewardship (educational tier, transparent pricing)

Estimated Total B Impact Score: 125-155 / 200 points

(Certification requires ³80 points; median certified B Corp: 90-100 points)

Note: Formal assessment pending revenue milestone. Current estimates based on self-assessment.

RESEARCH-BACKED METHODOLOGY & VALIDATION

Academic & Industry Partnerships (Planned):

We are establishing industry-academia collaborations to ensure rigorous, independent validation of social impact

claims:

Research Areas:

• Democratization studies: How AI systems can preserve "design intentionality" while lowering barriers to expertise

• Human-AI collaboration: Socio-technical requirements for augmentation (not automation) of craftspeople

• Accessibility research: Validation of disability inclusion features with actual users

• Circular economy: Economic viability of distributed production networks

Methodology:

• Designer user studies (target n=30-50)

• Longitudinal impact tracking (18-24 months)

• Ethnographic observation of fashion production workflows

• Economic impact surveys and case studies

• Accessibility testing with disability advocacy groups

Expected Outcomes:

• Peer-reviewed publications in fashion technology and HCI journals

• Open-access research data contributing to fashion tech literature

• Validated frameworks for other craft industries (furniture, electronics) to replicate model

Current Validation:

3 Solar Impulse Foundation: Lanfinitas AI currently in Showcase status (under evaluation for Efficient Solution Label

2026)

3 HarmonAIze (circular model): Solar Impulse Efficient Solution Label 2025 validates social + environmental impact

of artisan employment model

3 Designer interviews (n=8): Validated pricing accessibility and willingness to pay

3 Industry partnerships: Google Cloud for Startups, GPU Link (compute infrastructure support)

This positions Lanfinitas AI as research-backed rather than purely commercial, ensuring accountability to academic

standards for social impact measurement.

LIMITATIONS & TRANSPARENCY COMMITMENTS

Current Limitations (Pre-Revenue Phase):

• No actual user data yet (projections based on designer interviews n=8 and industry benchmarks)

• Economic impact calculations are estimates pending real client validation

• Disability accessibility features planned (not yet implemented; target Q2 2026)

• Employment projections assume successful scaling (subject to fundraising, market adoption)

• Geographic diversity targets depend on localization investments (multilingual support 2027+)

Transparency Commitments (Post-Launch Q1 2026):

3 Quarterly social impact reports (starting Q2 2026)

3 Annual comprehensive impact assessment

3 Open methodology (all calculations publicly documented)

3 Third-party verification once scale justifies cost (B Corp 2028 target)

3 User privacy protection (aggregate data only, opt-in demographic surveys)

Accountability:

We commit to revising projections if actual data diverges significantly from estimates. Social impact claims will be

updated based on real-world evidence, not aspirational goals alone.

Contact for Social Impact Inquiries:

Lu Min, Founder & CEO | littledesign.solution@gmx.us | www.boekovermij.com

Full impact assessment methodology and data sources available upon request.

Document generated: December 2025 | Version 2.0