Governed AI
CRM with human-approved AI
Useful AI in a CRM is not the kind that acts alone, but the kind that prepares work for a person to review and approve. AgentticCRM follows propose–approve–execute: the assistant proposes, inherits your permissions and cites approved knowledge; actions with consequences are always approved by a person.
What separates a read-only action from one with consequences?
| Read-only (automatic) | With consequences (needs approval) |
|---|---|
| Search and summarize information | Create or edit a client |
| Answer a question citing the knowledge | Issue an invoice or send a proposal |
| Prepare a draft for review | Change permissions or operation data |
How does propose–approve–execute work?
The assistant gathers the context and builds the full action —for example, the whole invoice— and presents it as a proposal. A person reviews it, adjusts it if needed and approves it; only then it runs. Nothing with consequences happens behind anyone’s back.
Why does it inherit permissions and cite sources?
Because an AI that sees more than the person using it, or that asserts without a source, is a risk, not help. The assistant stays within the same role limits as its user and grounds its answers in approved knowledge, so they can be verified. It is the practical application of the product’s security.
Where does this fit in the operation?
Across the whole operating CRM journey: preparing proposals, organizing projects, drafting support replies or getting an invoice ready. Always as a proposal, always with a person who decides.
Frequently asked questions
What is an agentic CRM?
A CRM whose assistant does more than answer: it prepares real work —a proposal, an invoice, a client record— and leaves it ready for a person to review and approve before it runs. The assistant takes initiative; the person decides.
Can the AI make changes without my approval?
No. Read-only actions (search, summarize, answer) happen on their own; any action with consequences goes through propose–approve–execute: the assistant proposes, a person approves, and only then it runs.
What does the AI see of my data?
It inherits the permissions of whoever uses it: it sees no more than that person could, and always within their organization. Its answers build on approved knowledge and can be cited.
See the AI that proposes and the person who approves.
We’ll show the propose–approve–execute model inside your operation.