Every bot conversation gets evaluated in real time. The ones that need a human — callback requests, unresolved issues, and low-confidence answers — land in the AI Escalation Queue with the AI's reasoning attached, and an email lands in your inbox.
Most chatbots leave a trail of conversations that quietly need human attention — callback requests with a phone number left behind, questions the bot couldn't answer, and replies the model wasn't confident about.
ChatBeacon catches all of it. The AI reads every transcript, decides what needs a human, writes a flag note explaining why, and routes it to the right queue.
Every flag falls into one of three buckets — color-coded across the queue, the emails, and the operator console. No taxonomy to maintain, no rules to write.
The queue lives inside the Operator Console — live, auto-refreshing, filterable by priority and queue. Each card carries the AI's flag note and full transcript, ready for one-click claim.
Bot conversations flagged for human follow-up
Every flagged chat flows the same way — evaluated, classified, queued, and emailed.
Every bot conversation gets scored in real time — model confidence, intent, sentiment, and whether the visitor explicitly asked for a callback.
Chats that need a human get classified into one of three types — Callback, Unresolved, or Low Confidence — with a plain-English flag note.
The flag lands in the AI Escalation Queue and a system email goes out to the right inbox (sales, support, or billing) within 30 seconds.
Your agent opens the queue, sees the transcript, the AI flag note, and the suggested next step — then claims, calls back, or replies.
The moment the AI flags a conversation, ChatBeacon emails the right inbox automatically — with the AI's reasoning, the visitor's contact details, and a one-click jump back into the queue.
It reads every turn in real time and evaluates the conversation across multiple signals — model confidence, intent, sentiment, whether the visitor asked for a callback, and whether the bot hit a knowledge-base gap. When the AI determines a human is needed, it classifies the chat into one of three flag types (Callback, Unresolved, Low Confidence) and writes a plain-English note explaining the reasoning.
Callback Requests (visitor left contact info asking for follow-up), Unresolved Issues (the bot couldn't answer — no KB content, platform bug, escalation needed), and Low Confidence Responses (the bot answered but with confidence below threshold, so the response may need verification).
Every flagged conversation in one live queue — KPI tiles up top (open events, callback requests, unresolved issues, low confidence), priority filters (urgent / needs attention / informational), and queue filters (sales / support / billing). Each event card shows the AI flag note, the full transcript, visitor details, and one-click actions (claim, assign, snooze, dismiss).
The moment the AI raises a flag. The email goes to whichever inbox matches the queue (sales@, support@, billing@) and contains the AI's flag note, visitor contact details, and a one-click link back to the dashboard.
Fully AI-based. The model evaluates each conversation holistically — you don't maintain keyword rules, decision trees, or escalation thresholds. The AI reads the transcript in context and decides what needs a human.
No. The queue, email notifications, and AI-cited flag notes are part of every ChatBeacon AIX plan — including Starter. No per-flag fees, no upgrade required.
Spin up a free trial, point your bot at your knowledge base, and watch the queue light up with real conversations.
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