ReactLive Agents

An AI event team. Under your control.

ReactLive uses three specialist agents with narrow responsibilities. Protect keeps participation safe, Answer handles questions from event knowledge, and Engage watches the room. They work the same event together — and you decide how far each one goes.

How the agents work together

Three narrow jobs. One live event.

The agents do not take turns, and there is no fixed order. Anything can arrive at any moment, and every contribution is analysed by all three at once — each through its own job — with your team deciding what happens next.

  1. 01 · Arrives

    Any contribution

    A question, comment, reaction or poll response — from the Audience app or the Event Page, at any moment.

  2. 02 · Analysed by all three, at once

    Protect

    Is it safe for the room? Clears it, or holds it for a moderator with the reason attached.

    Answer

    Can event knowledge answer it? Drafts a sourced answer, or spots a duplicate.

    Engage

    What does it say about the room? Votes, themes, participation — a spotlight, a poll, or nothing.

  3. 03 · Decided

    Your team

    Approves, edits or dismisses what the agents found. In Auto, only the actions you approved in advance happen without a click.

One event, shared context

All three read the same queue, the same event knowledge and the same moment In Focus. Engage can see that Answer has already resolved a question before it suggests spotlighting it.

Held means held

Something Protect holds stays with a moderator. Engage cannot release it and it does not reach the room — only a person can let it through.

No overlapping authority

Engage engages, Answer answers, Protect moderates. None of them can do another’s job or undo another’s decision, so there is never a question of which agent is in charge.

Each one set on its own

Working together does not mean switching on together. Protect can run in Auto while Answer and Engage stay in Assist — see a real configuration.

AI control

Start with assistance. Automate only what earns your trust.

Every actionable agent is controlled independently. You are not switching “AI” on. You are deciding what each agent is allowed to do at this event.

Off

No AI involvement. The agent does not observe and does not act.

Assist

ReactLive observes and recommends. A human approves consequential actions before they happen.

The safest place to start.

Auto

ReactLive may perform approved types of work automatically within defined guardrails. The event team remains able to take control at any time.

A realistic configuration · quarterly all-hands
Engage OffAssistAuto Publishing to the room stays a human decision
Answer OffAssistAuto Answers are approved until the sources are trusted
Protect OffAssistAuto Holding is reversible, so automation is low-risk

Why this configuration

Engage and Answer run in Assist because publishing to a live audience is not reversible. Protect runs in Auto because holding content is reversible and the cost of missing something is high.

Teams typically move an agent to Auto only after several events where its suggestions were consistently approved unchanged.

You do not switch “AI” on or off. You decide exactly what each agent is allowed to do.

Human authority

Humans outrank agents.

ReactLive is built for live environments where mistakes matter. These are the rules the system holds itself to.

Humans outrank agents
A deliberate human decision is not quietly overridden by automation. If a moderator released something, an agent does not re-hold it behind their back.
Agents have narrow responsibilities
Engage engages. Answer answers. Protect moderates. No agent has unlimited authority, and none of them can do another’s job.
Actions are visible
Operators can see what an agent suggested, what it did, why it acted, its confidence where relevant, and what required human approval.
Answers are grounded
AI answers use trusted event material. No source means no automatic answer.
AI is explicit
ReactLive does not pretend AI-generated output came from a human moderator or speaker.
Safe failure matters
If a risky contribution cannot be safely evaluated, the system favours review over blind publication.

Put the agents to work at your next event.