Hi all,
After receiving some initial feedback on my evidence earlier this year, I’m posting an updated list of my revised evidence. I have made substantial changes based on your earlier feedback (removing weak evidence, merging related items, adding third-party verification, clarifying innovation vs impact, etc.). Below is my final structure. Would appreciate any guidance before I submit.
Mandatory Criteria (MC)
MC1 – Speaking Recognition (International + UK)
Evidence combined:
- Data Innovation Summit 2025 (Stockholm) — invitation email, agenda listing, badge/photos, event stats (3,500+ delegates, 1,500+ companies, attendees from 70+ countries).
- GirlsWhoML London Featured Speaker — (I spoke about my experience and insights building startup) Luma event link, 53 attendees (majorly women), unsolicited attendee post praising my insights, before/after LinkedIn engagement.
How this meets MC1:
Shows a pattern of recognition (not a one-off), one high-profile international event + one UK community event with external validation.
MC2 – Prestigious Accelerator Selections
- Soonami Accelerator — acceptance email, “Top Team” email, demo-day investor introductions.
- Antler Final Selection — final round selection email (<3% acceptance rate).
How this meets MC2:
Competitive merit-based selection demonstrating external industry recognition.
MC3 – Hyperledger Open Source Contribution (Linux Foundation)
- <7% acceptance global open-source internship (LFOS).
- Contributions to Hyperledger Climate Action & Accounting SIG.
- Merged PRs, CI/CD pipeline improvements, later contributors referencing my work.
- Project later integrated into IBM Call for Code 2022 winner.
- GitHub history showing multi-year contributions to major open source projects (dating back to 2019).
How this meets MC3:
Significant contribution to an open-source digital tech project with external validation, recognised by maintainers.
Optional Criteria 1 (OC1) — Innovation
OC1-A – SavrAI Product Innovation
- Proprietary AI reasoning engine (deal-breaker rules, decision trees, domain-specific logic).
- Cost-per-wear intelligence module.
- Architecture diagrams + code excerpts (non-confidential).
- Third-party validation: accelerator selection + investor engagement.
OC1-B – Sony “kikAI” Automation System (Innovation inside employment)
- First AI-based computer-vision automation system for BRAVIA testing.
- Core technical design: image pipeline, CV workflows, automated multi-model testing.
- Adopted across 22 European regions for every BRAVIA release since 2022.
- Third-party verification: letters from ex-Divisional Director + senior engineer (also a stakeholder).
Optional Criteria 3 (OC3) — Impact
OC3-A – SavrAI Commercial Traction
- Stripe payment confirmation (first customer payment).
- Google Analytics: ~570 new users + 95 returning, 100% organic traffic.
- Global adoption across cities (UK, US, UAE, India).
- User testimonials and unsolicited inbound interest.
- Investor interest (emails confirming deck reviews + follow-ups).
OC3-B – Sony TV Channel Editor App (Launched to 100K+ users)
- Led end-to-end release-readiness and verification engineering.
- 64+ test cycles, 231 issues coordinated.
- App reached 100K+ downloads across EU with postive reveiws on PlayStore/appstore and zero critical post-launch issues.
- Received Sony FY22 Technical Excellence Award (internal recognition for engineering quality).
OC3-C – kikAI Requirements Delivery (High-impact internal contribution)
- Delivered 50+ cross-functional automation requirements for testing across 22 markets.
- Included handling a major escalated market quality issue: 4 weeks → 2–3 days reproduction.
- Verified by senior engineer (the requirement stakeholder) in reference letter.
Would appreciate feedback on:
- Whether MC3 (Hyperledger open source contribution) is placed correctly or should it go as OC2.
- I merged speaking at 1 high-profile international conference (Data innovation) with 500+ attendees and one other GirlsWhoML event I hosted and spoke at in the UK (national level) with <100 (53) attendees but with high impact, with MC1. Does that make MC1 stronger?
- Whether having two OC1 + three OC3 evidences is acceptable or should I limit to exactly two per criteria.
- Any red flags remaining or areas needing further strengthening.
Thank you all again for your time and support!