Hi everyone! Thank you for all the valuable guidance this forum has provided. I’m preparing my GTV Exceptional Promise application and would appreciate feedback on my evidence structure and strength.
Background
AI/ML Engineer with 4+ years experience, applying under Exceptional Promise route. Seeking review of evidence organization and whether achievements meet the bar for endorsement.
MANDATORY CRITERION
Requirement: Recognition as potential talent in digital technology field (last 5 years)
Evidence:
MC-1: First-author paper at top-tier AI conference (NAACL international conference) + presentation video hosted on conference website
MC-2: Peer reviewer invitation and completed reviews for another major AI conference (screenshots from review system)
OPTIONAL CRITERION 1 - Innovation as Founder
Requirement: Show innovation as founder of product-led digital technology company
Evidence:
OC1-1: Company incorporation documents showing co-founder status + shareholding certificates
OC1-2: Google Analytics report: 65,000+ users in 1 month after beta launch (Dec 2024)
OC1-3: Product screenshots + technical architecture documentation for May 2025 relaunch showing innovative improvements
OPTIONAL CRITERION 2 - Sector Contributions
Requirement: Contributions to digital technology sector outside of work
Evidence:
OC2-1: Kaggle profile screenshots showing Master (Notebooks) + Expert (Datasets) status with 10 silver, 6 bronze medals
OC2-2: Dataset screenshot showing 2.7K+ downloads with community engagement metrics
OC3-1: Employment contract + company website showing role as first technical employee in the firm who made the first version of the tool
OC3-2: Git commit logs
OC3-3: Client testimonials showing measurable business impact. Customer feedback claiming tool saved weeks worth of analysis time.
OC3-4: Revenue projections showing £1M+ by end of year + proof of commercial success
LETTERS OF RECOMMENDATION
LOR 1: Lead AI Engineer, current employer (10+ years experience)
Relationship: Direct supervisor for 8 months. A university senior who was referred by me to the company
Focus: Technical leadership in £1M platform development, innovation in AI feedback processing
LOR 2: Professor of Artificial Intelligence (Academic institution)
Relationship: Research collaborator familiar with publication work
LOR 3: [SEEKING ADVICE] Currently planned: Co-founder (4 years experience)
Concern: Wondering if 4 years experience is sufficient, I wanted to ask my CEO for the LOR but he is from a non-technical background and since the startup is bootstrapped I am afraid no fund raising or startup accelerator.
SPECIFIC QUESTIONS FOR COMMUNITY
Evidence Strength: Are these achievements sufficient for Exceptional Promise endorsement?
Criteria Alignment: Have I structured evidence correctly against official criteria? Any overlaps to address?
LOR Concern: Is my third referee too junior? Should I replace with:
Client who uses our platform and can speak to business impact?
Industry expert/senior researcher who knows my work?
Evidence Gaps: Any critical evidence missing that would strengthen the application?
Document Organization: Should I combine any evidence pieces or separate them differently?
ADDITIONAL CONTEXT
Timeline: Planning to submit in next 2-3 weeks Previous Applications: First-time applicant
Any feedback on evidence strength, structural improvements, or general advice would be greatly appreciated. Happy to provide more specific details on any evidence piece if helpful for assessment.
Hi @Rushikesh_Hiray It will help for people to give feedback if you can share an outline citing the criterias you are attempting from the guideline clearly and what kind of evidences under each criteria. Please refer to other posts on the forum to see outline samples.
Hey @pahuja. Thank you for the quick reply. I have updated my question properly. please let me know if there is any other information I should share. Thanks.
You can only apply for two OCs and not three so you will have to select. I would recommend one of the OC evidences to MC.
In OC1: your 2nd evidence doesnt reflect what was innovative about this and what was your contribution to it. Moreover all 3 evidences look snippets of 1 single large project? If so you should combine. On their own, each document should be able to show innovation and your role in it. Innovative improvements arent really strong, strong innocations are required.
OC3 - 1st whats the impact of this in company metrics? How is it validated? OC3.3 if you can get a reference letter instead that is deeper and shows your contribution would be better. OC3.4 is projections but not actual success yet hence is weak. OC3.2 doesnt show any quantified impact? It is unclear currently from your overall OC3 what has been the quantified impact of your contributions.
Your evidence list has potential but lacks alignment with criteria fully and you need to strengthen those by strong positioning, letters, third-party validations and quantified impact on company metrics and the industry.
for OC1 - Understood. I will combine the evidences and shift this up to MC.
for OC3 - OC3.1 - I assumed the mention of me being the first engineer on the project who made the necessary POC’s will somehow highlight my skills more. The company site has a component that shows the team info. My description besides the photo mentions it along with mentioning me as a vital member of the team. Will that be enough or is it better I get a reference letter from my CEO highlighting my impact ?
for OC2 - I have uploaded multiple datasets and notebooks on Kaggle. One of my dataset contributions was a unique dataset I scrapped off a bunch of sites which got some high traction. Another user who sited my dataset as his inspiration created an enhanced version of it. This enhanced version was later used in a phd thesis and inspired a bunch of community engagement including dashboards and visualizations with over 9k downloads. Since my dataset was sited as the primary inspiration do you think I can add that as community impact. The enhanced dataset’s description has a direct mention of my work and a link to my original post.
Again, thank you so much for the quick replies. Really appreciate all the help
Being one among the team more often than not gives an impression that the impact was also because of the team collectively and cannot be attributed solely to your contribution. Please don’t leave open ends for assumptions, it’s always better to tie up strongly and own the narrative than let them assume and flag. A reference letter from the ceo highlighting your personal significant contribution and impact is much stronger.
Your application has strong potential, but there are areas where you can improve alignment with the criteria. For the Mandatory Criterion, ensure your evidence clearly demonstrates recognition as a potential talent. For example, your first-author paper and peer review contributions are excellent, but you should emphasize their impact on the field and include third-party validations, such as citations or testimonials from respected professionals.
For the Optional Criteria, focus on two that best showcase your strengths. If you choose innovation, ensure your evidence highlights your unique contributions and the tangible impact of your work. For example, instead of just showing user growth, explain how your innovations drove that growth. Similarly, for sector contributions, emphasize the community impact of your Kaggle datasets, especially the one that inspired further research and tools. Include metrics and testimonials to strengthen your case.
Lastly, your Letters of Recommendation should come from individuals who can vouch for your technical expertise and impact. If your CEO can provide a letter detailing your contributions and their significance, it would be stronger than a junior co-founder. Avoid leaving room for assumptions by clearly tying your narrative to the criteria. This approach has worked well in other successful applications I’ve seen.