The situation
FounderCrush is a company I co-founded and run as CTO. It is an agentic AI co-founder for entrepreneurs: it helps with company formation, compliance, banking, insurance and operational setup.
That is sensitive ground. An agent that can act for someone near their bank account and their personal details has to earn trust before it can be useful. Getting that wrong would not be a bug. It would be the end of the product.
What I did
I built it on Mastra AI, with tool-calling agents and RAG pipelines. In plain English: the agents can take actions, not only answer questions, and they answer from trusted documents instead of guessing.
Responsible AI was part of the design, not a policy written afterwards:
- Explicit consent flows, so a founder agrees before agents act on their behalf.
- Least-privilege agent permissions, so each agent can reach only what its task needs.
- Audit trails, so agent actions can be checked later.
- Human approval before any access to sensitive financial or personal data.
The business model follows the same thinking. FounderCrush earns through referrals to service providers rather than subscriptions, so it makes money when it helps a founder get something done.
The result
- users in the pilot so far
- 100+users in the pilot so far
A pilot is not a finished story, and I will not dress it up as one. What it shows is that agentic AI can be useful and careful at the same time.
What it means for you
If you want AI in your product, the question is not whether the model is clever enough. It is what the AI is allowed to do, who approves it, and how you would know if it went wrong.
I help founders find where AI pays back and build it with sensible guardrails, usually as an Innovation Build that ships a working version in four weeks. If you want to read first, here is how to add AI to your product without the risk.