Aayush Bhan
Agentic AI Engineer
AI 
Transparency.
Show what a system can do, why it decided, and where the content came from.
AI Transparency.
Explain consequential decisions
A decision that affects someone is given with no explanation.
Identify decision factors
The factors that moved the decision are hidden.
Expose relevant limitations
Users are not told where the decision is weak.
Communicate decision uncertainty
A consequential decision is presented as certain.
Disclose AI capabilities
Users are not told what the system can actually do.
Disclose AI limitations
Limits are missing from the description people rely on.
Identify system boundaries
It is unclear where the system stops and a person or another tool begins.
Communicate operating conditions
The system is used outside the conditions it was cleared for, and that is never stated.
Explain model outputs
An output arrives with no account of why.
Explain agent actions
Tool use and steps are invisible to the person accountable for them.
Provide user-understandable explanations
Explanations exist, but a non-specialist cannot use them.
Validate explanation quality
Explanations can be fluent and still wrong.
Track content origin
Generated or edited content has no record of where it started.
Track data provenance
Data moves through the system without a record of its source.
Verify transformations
Edits and model passes are not checkable against the original.
Preserve provenance across systems
Origin is lost when content moves to another product.
Identify AI-generated content
Synthetic text, image, or audio is presented as human-made.
Disclose AI involvement
A person is not told that AI produced or shaped what they are seeing.
Inform users about AI interaction
Users talk to a system without being told it is AI.
Prevent deceptive AI representation
The system is presented as a person, an institution, or a source it is not.
Pick a challenge
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Pick a challenge
Build a solution
Win prizes
Showcase to experts
Pick a challenge
Build a solution
Win prizes
Showcase to experts
Build with purpose.
Challenges are aligned with the United Nations and USAID Sustainable Development Goals. You're not just learning, you're working on problems that reflect real-world needs.
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Get guidance from industry professionals.
Gio Masawi
Global Solutions Manager Gemini Enterprise, Agentic AI
Karina Assini Andreatta
Senior Data Scientist, AI Engineer
Casius Sibanda Lee
AI Developer Advocate
Geoffrey Rolin Jacquemyns
Claude Ambassador
Anubhav Pandey
AI Product Manager, Forward Deployed Engineer
Gain invaluable insights and support from seasoned experts who are passionate about driving positive change. Our mentors bring years of experience in tackling complex challenges, ready to share their knowledge and help you make a meaningful impact.
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Collaborate with like-minded.
Choose your challenges and connect with like-minded peers. Work together to tackle crucial social, environmental, and governance challenges with expert guidance.
Tobias
Maria
Ariya
Eugene
Jury Panel
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Winner
Finalist
Finalist
Tech partner
The winner and two finalists will receive Exa.ai credits and cash prizes (TBD), exposure through Exa’s developer community, and technical support to help develop their projects further.
Nominees
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FAQ
Learn more about the challenge
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Anyone can join, no matter your background or experience level. Whether you're a student, recent graduate, or transitioning careers, this platform is designed to help you build real-world skills. We welcome diverse perspectives, including scientists, designers, engineers, analysts, marketers, educators, and more.
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Yes, participation is completely free.
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- Follow guides to solve the problem (solo or in a team).
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Are there any deadlines?
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Can I participate as part of a team?
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Can participants apply multiple times?
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