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    Production AI agent · Flexible tool use

    SerniaAI operations agent

    An AI agent that helps the property team work across conversations, tasks, and follow-ups, with persistent context and approval gates for sensitive actions.

    The operational problem

    Property operations arrive as fragments: a text from a tenant, an email thread, a pending task, or a reminder. The team needs a way to connect those details and act without reconstructing the history every time.

    How a run works

    1. 1Trigger

      Chat, event, or schedule

      A team member asks a question, a supported event arrives, or a scheduled check starts a run.

    2. 2AI judgment

      Gather context and plan

      The agent reads relevant history and business knowledge, then selects tools for the task.

    3. 3Controlled actions

      Execute within permissions

      Application tools validate operations. Actions that require approval pause for human review.

    4. 4Outcome

      Reply, act, or wait

      The team gets a response or follow-up. The conversation records context for the next run.

    Where AI decides

    The agent determines which information matters and which tools to call. It can search communications, consult its workspace knowledge, manage tasks, and coordinate follow-ups rather than following one fixed sequence for every request.

    What the code controls

    Authentication and internal-contact checks govern entry points. Tool implementations enforce permissions and approval rules. Conversation persistence and scheduled jobs live in application code, outside the model’s reasoning.

    The practical outcome

    The same operational context can carry from a web conversation to an internal SMS thread or a later follow-up. The assistant can also stop without taking action when a trigger does not need a response.

    This is the private operational system. The public agent demo uses a separate, restricted workflow and does not expose tenant records or business tools.