FlowClick's agent isn't a chatbot bolted on the side. It has governed access to your data, flows, files, models, and configuration — and every action it takes runs under someone's permissions, inside a budget, and onto the record.
Talk to it in an app, call it from a flow, or let it run as a job. It can read and write records, trigger flows, generate documents, send messages, browse the Marketplace, and change your application — through the same permissioned tools your team uses.
agent step inside a workflow, or an in-process jobMost "AI agents" have all-or-nothing access and no memory of what they did. FlowClick's agent is a principal in the platform's security model, and it is held to it on every single tool call.
Every tool executes with the invoking user's identity, group memberships, and token scopes. The agent can never do more than the human who started it — the same PermissionEvaluator that guards the API guards the agent.
Declare per-account caps on classified side effects — outbound email, SMS, push, payments, external calls. The executor decides allow, warn, escalate, or refuse before the step dispatches, and writes an audit row for each decision.
Run any agent under a QA session and its side effects are captured, not fired — so you can test what it would do. Put a human task in front of irreversible actions; row protection and retention holds apply to the agent like anyone else.
Chat, job, or in-process, each invocation is a durable AgentRun — principal, provider, tools called, outcome — joined to the trace of the flow that started it and the audit rows it produced.
Cancel any running agent job, cooperatively and immediately. Per-account caps on concurrent jobs and tool calls per run bound the blast radius of a runaway loop, and provider failures fail closed.
When the agent wants to change an application, connector, mapping, or flow, it files a proposal. The platform validates it against real evidence and a person approves it. The self-building loop →
The agent loop is provider-agnostic. Native wire adapters for Anthropic, OpenAI, Google Gemini, and xAI Grok plug into one execution loop, so a flow written today runs on whichever model you choose tomorrow.
Classify inbound tickets and email, draft replies in the customer's language, update the record, and route to the right team — with a human task before anything goes out to a VIP.
Reconcile invoices against orders, chase overdue accounts within an email budget, and raise exceptions as human tasks with the evidence attached.
Ask for a connector to a new vendor or a mapping between two schemas. The agent drafts it, the platform tests it, and you approve it — the integration builds itself.
Bring a process with real side effects — emails, records, approvals. We'll run it with an agent inside and show you every decision on the record.