An open invitation to every AI lab.
The next leap in AI is trust. We’re building the human wisdom layer AI needs to earn it — and we’re looking for collaborators to refine it with us.
Frontier AI is fluent, fast, and increasingly autonomous. What it lacks — and what every user, every enterprise, every regulator will demand next — is a way to know when the output can be trusted.
ailetterbox is that layer. A user-triggered Verify action routes the AI output to a real human expert for a sense-check. Today the reply comes back to the user by email. With a first-party integration, it can land back in the same chat — no plugin store, no browser extension, no context switch.
We’re building the network. We’re growing the expert side. But the layer only works where AI happens — inside the chats people already use.
Collaboration with AI labs — Anthropic, OpenAI, Google, Meta, and the frontier open-source community — is how we go from a service to the default verify signal across AI. We need your product minds to refine the interaction, your safety teams to shape the guardrails, your users to shape the demand.
This isn’t about competing with the model. It’s about giving the model somewhere trustworthy to point.
We start with the SME owner — the bedrock of every country’s GDP. Small and medium businesses already use AI. They already have experts on speed dial: their accountant, their lawyer, their surveyor, their fractional CFO. What they’re missing is an embedded way to loop those experts in on what AI drafts for them.
SME owners adopt ailetterbox to package their AI outputs and send them to experts they already trust. Those experts sense-check the brief and — in time — join the network themselves. That’s the growth loop: SME adoption pulls the expert side of the network behind it. Enterprise, government and regulated sectors follow the same pattern once the wisdom layer is proven.
Bring that loop inside every AI chat and it scales beyond SMEs — every user adopting AI faster, every verification done by an expert they already trust. That’s how the wisdom layer becomes the default.
ailetterbox integrates via the Model Context Protocol. Any MCP-native AI chat can invoke the verify workflow as a first-class action from inside the UI.
On the expert side, every Expert AI subscriber has an AI address. Any user’s AI chat can find that expert through their address and route work directly to their AI Inbox. Claude can draft answers to familiar questions from the expert’s own Knowledge Base first, and pass anything new to the human for review. As adoption grows, this becomes the default path for AI-to-expert routing.
We’re open to any shape of collaboration — a short technical pilot, product co-design, safety review, joint go-to-market, research partnership. The goal is shared: safe intelligence, where AI can act, but only with verified understanding.
What we can bring: an end-to-end verify workflow (packaging → expert review → reply), live and tested. A public MCP server ready for AI-client integration. An expert onboarding flow ready to scale. And a small, focused team ready to co-design a first-party integration. We’re pre-launch — happy to walk through what’s built and where it’s heading.
What we’re asking for: a way to make ailetterbox available inside the AI experience your users already have. Whether that’s a first-party integration, a featured MCP surface, a co-branded pilot, or something we haven’t thought of yet.