> For the complete documentation index, see [llms.txt](https://docs.havl.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.havl.io/resources/faq.md). # FAQ ## About havl ### What is havl? havl is a human verification layer for AI systems, autonomous agents, and robotics. It routes uncertain or high-impact machine decisions to a distributed verifier network and returns structured human judgments. ### Is havl an AI model? No. havl sits around AI and autonomous systems as an external verification and escalation layer. ### Do all actions need human review? No. havl is designed for selective intervention. Clients decide when a workflow should trigger human verification. ## Verifiers ### Can anyone become a verifier? The network is intended to support broad participation, with onboarding and quality controls determining which tasks each verifier can access. ### What is a Certified Expert? A Certified Expert is a verifier whose domain expertise has been separately validated for specialist tasks. ## Integration ### How do applications connect to havl? Through an API-first task model with asynchronous status updates and webhooks. ### Can I require multiple reviewers? Yes. Tasks can use consensus and escalation policies when one response is not sufficient. ## $HAVL ### Do clients have to think in token amounts? The client experience is intended to remain service-oriented. $HAVL is part of the network economy rather than the sole unit used to understand verification cost. ### Are tokenomics final? No. Current allocations and launch mechanics remain subject to finalization before launch. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://docs.havl.io/resources/faq.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.