The problem isn't a lack of ideas. It's a lack of connection.
ProblemBank connects real-world problems with people who have the skills to work on them, and keeps an honest, reviewed record of what actually happened.
Our mission
People run into problems every day that someone else could help solve. Meanwhile, capable people look for meaningful work. ProblemBank sits between the two: problems come in, get structured and reviewed, and are matched with people who can form a team and build, test and measure a solution.
The lifecycle
- A problem is submitted with who it affects, why it matters and any evidence.
- AI gathers context and flags gaps; a ProblemBank reviewer verifies it, asks for more, or declines it.
- Verified problems are discoverable. People propose solutions, which are also reviewed.
- A team forms, plans tasks and milestones, and submits evidence as work completes.
- ProblemBank approves development before testing, and reviews test results.
- Impact is submitted with evidence and only becomes "verified" after a human review.
Human verification principles
- AI researches. Humans decide. AI can summarise and recommend, but it can never approve, verify or mark anything solved.
- Official decisions are enforced by the platform itself, recorded with the reviewer and their reason, and kept in an audit history.
- Teams cannot approve their own development, tests or impact.
- Payment or sponsorship never buys verification. Participation is free.
Where we are today
ProblemBank is early-stage. Some records are clearly labelled demo examples so you can see how the journey works; they are not real outcomes and never count towards verified impact. Everything else comes from real accounts. We don't publish user counts, partnerships or results we can't back with reviewed evidence.