Safer Broadcast Sends
Draft an emergency alert in seconds from a scenario template, see the audience preview and predicted ack curve before you dispatch, and confirm every send explicitly. Cancel an in-flight alert, withdraw a pending approval, and generate a compliance-grade incident summary after — all without leaving Ask AI.
Why Emergency Sends Break Under Pressure
Broadcasts & Alerts Admin Agent attacks the four specific failures that turn a critical send into a 20-minute scramble — without taking the human out of the decision to dispatch.
Drafting An Alert Mid-Incident Is The Wrong Time To Compose
Severe weather closure, system outage, lockdown — the admin needs to compose a tight, multi-channel message in under two minutes while the incident is still active. Starting from a blank screen is how typos and wrong recipient counts ship.
Audience Is Always Bigger Or Smaller Than It Looks
"All employees" sounds clear until someone notices half the field workforce isn't in the default audience, or the segment includes ex-employees who shouldn't get an internal alert. Without an audience preview on the confirmation, the surprise lands in inboxes.
Predicting Reach Is A Coin Flip Without Past Data
Quiet hours, channel preferences, and device-token freshness all shape whether a send actually lands. Admins guess; the agent grounds the prediction in similar past sends.
Post-Send Documentation Eats An Hour Per Incident
Compliance asks "what went out, when, to whom, with what outcome?" Without a structured lifecycle narrative, the answer is a manual sweep across deliveries, acks, and muster — every single time.
A Misfire Is A Resignation-Level Event And There's No Undo Button
Send the lockdown alert to the wrong building, send a payroll-error message to "All Employees" by mistake, or fire a "test" template at production at 2am — and the conversation the next morning isn't about the typo, it's about who hits send and how. Without an in-flight cancel, a pending-approval withdraw, and an explicit confirmation on every dispatch, the admin is one click away from a career-defining mistake.
Approval Chains Stall Right When Speed Matters Most
Critical alerts often need a second signoff — safety lead, communications director, legal for sensitive language. The approval request goes out, the approver is in a meeting, and the alert sits pending while the situation evolves. Without an agent that can prepare the package, route the approval, and surface stall states in chat, the bottleneck is the inbox nobody's watching.
Broadcasts & Alerts Admin Agent At A Glance
Broadcasts & Alerts AI (Admin)
Drafts and sends with audience preview, predicted reach, and explicit confirmation.
Inside Broadcasts & Alerts Admin Agent — The Actual Capabilities
Every block below maps to a real tool the agent uses against your Broadcasts & Alerts data. Every write is in RISKY_TOOLS — drafts are previewed, sends are confirmed, cancellations are explicit. The agent never dispatches silently.
Draft Alerts From Scenario Templates, In Plain English
"Draft a severe weather alert closing the office at 2pm" — the agent pulls the right scenario template (severe_weather_closure, lockdown, IT outage, etc.), pre-fills channels, SMS-shortened body, urgency, and ack-required flags. The output is a DRAFT, not a send. Nothing leaves until the admin confirms.
- compose_alert — title, body, sms_body, channels, urgent, ack_required, safety_check_in, audience_id, scenario_template. Creates a DRAFT only.
- compose_broadcast — formal announcement (not emergency-grade), critical flag, ack-required option.
- scenario_template — pulls from ScenarioTemplateRegistry (severe_weather_closure, lockdown, IT outage, evac drill, etc.) and lets admin overrides win.
- RISKY by design — both compose tools are gated; the model can't draft without surfacing the draft for approval.
Audience Preview, Predicted Reach, Confirmation On Every Send
Before send_alert_now fires, the agent surfaces the audience count, channel breakdown, quiet-hours overlap, and a predicted ack-curve from similar past sends. The admin sees the size of the blast and the reach forecast in one card, then confirms or cancels. Approvals can be withdrawn before they're cleared.
- send_alert_now — promotes a draft from status=draft to sending and enqueues the fanout. Confirmation required.
- cancel_alert — sets status=cancelled on a draft or in-flight alert. Confirmation required.
- withdraw_alert_approval — pulls back a pending approval request so the alert can be edited and resubmitted.
- predicted_ack_curve — read-only forecast of expected ack rate + quiet-hours overlap, ground in similar past sends.
Post-Incident Summaries For Compliance, Generated From The Lifecycle
After a sent or cancelled alert, summarize_incident reads the lifecycle events, delivery roll-up, and muster outcomes and produces a compliance-grade narrative — author, channels, audience, dispatch time, ack progression, delivery failures with reason codes, and muster results. The tool is read-only and doesn't change state.
- summarize_incident — read-only post-mortem narrative for one alert id. Lifecycle + deliveries + muster, no state change.
- Lifecycle-grounded — pulls from the alert's actual event log, not the model's memory of what happened.
- Audit-friendly format — generated text is structured for compliance reports and incident reviews.
- Pairs with the Help Agent — read-only diagnosis (diagnose_delivery, muster_status) lives in the sibling agent for inspection without write reach.
Outcomes Teams Can Measure
The agent's job is to compress drafting time during incidents, surface the right audience and reach forecast before every send, and make post-send documentation a 30-second task instead of an hour. Measure against your pre-agent baseline.
- Time-to-draft during incidents — seconds from "we need to send an alert" to a structured draft ready for confirmation.
- Pre-send forecast adoption — share of sends where the admin reviewed predicted_ack_curve before confirming.
- Audience-mismatch incidents — sends where the audience count surprised the admin; should trend to zero as the preview becomes habit.
- Send-to-ack convergence — actual ack curve vs predicted curve; the closer the alignment, the more trustable the forecast.
- Post-incident documentation time — minutes per incident saved by summarize_incident vs manual narrative writing.
Write Actions, Always With A Human In The Loop
Broadcasts & Alerts Admin Agent's RISKY_TOOLS list is 5 entries — compose_alert, compose_broadcast, send_alert_now, cancel_alert, withdraw_alert_approval. Every one requires explicit user confirmation. The agent drafts, previews, and proposes; the admin presses send.
- 5 RISKY_TOOLS — compose_alert, compose_broadcast, send_alert_now, cancel_alert, withdraw_alert_approval. All confirmation-gated.
- Drafts before sends — compose tools produce status=draft only; dispatching is a separate explicit step.
- Audience preview required — the confirmation card surfaces the audience size, channel breakdown, and quiet-hours overlap before the admin commits.
- Audit trail on every action — every write logs the requesting admin, tool, parameters, and timestamp on the alert record.
WHAT TEAMS TRY INSTEAD
The four alternatives — and why none of them dispatch with audience preview, predicted reach, and explicit confirmation
Comms, security, and ops admins reaching for "AI broadcast composer" usually try one of these four. None of them combine scenario templates, audience preview, and a confirmation-gated dispatch in one Ask AI thread.
Pasting incident details into ChatGPT, Claude, or Copilot
Drafting an alert in a chat window, then copy-pasting into the broadcast tool
- Audience and predicted reach come from real device-token freshness and past sends — generic AI can only guess
- Dispatch happens inside the agent, not via a copy-paste step that loses the draft's context
- In-flight cancel and pending-approval withdraw are built in — a generic chatbot has no notion of an active send
Everbridge AI / PagerDuty AIOps / AlertMedia
Vendor-trapped mass-notification AI inside one alerting platform
- Composes with Comms Hub, Safety Hub, and Platform Admin — not stuck inside one alerting vendor's surface
- Audience is the same one used by the rest of HR, scheduling, and field-service apps — no parallel contact list to sync
- One agent across emergency alerts AND routine comms; no second contract for the non-emergency channel
A custom alert-composer bot on top of a notification API
An engineering team's six-month build, then forever maintenance of audience logic and approval routing
- Shipped already. Engineering spends zero weeks plumbing audience preview, quiet-hours overlap, or predicted reach
- All five writes are confirmation-gated by design — security review is a one-pager, not a multi-quarter audit
- Inherits new capabilities (richer reach prediction, new scenario templates) as the platform evolves
The manual fallback — compose a fresh alert from a blank screen
The default when a severe-weather closure is on the line
- Scenario template + draft generation lands in under 30 seconds — not a five-minute composition under pressure
- In-flight cancel and pending-approval withdraw stop a misfire from becoming a resignation-level event
- Post-incident summary writes itself from the lifecycle record — not a manual sweep across deliveries and acks
PLATFORM LEVERAGE
Broadcasts & Alerts Admin Agent inherits everything the platform already runs
A standalone alerting bot has to plumb each of these. The admin agent gets them for free because Comms Hub, Safety Hub, and the broader platform already do.
Cross-app data plane
HR audience segments, scheduling rosters, safety-hub muster, and platform-admin policy all reach the same agent — no separate sync between alerting and the rest of work.
Unified permission model
Only authorized admins can compose and dispatch; the agent inherits the existing alerting permission model — no parallel ACL to keep in sync.
Audit trail on every action
Every draft, send, cancel, and withdraw logs the requesting admin, tool, parameters, and timestamp on the alert record — same retention as the rest of the platform.
Translation in 100+ languages
Multilingual workforces get the alert in their language at dispatch time — same translation service that powers Chat, Policies, and SOPs.
Mobile delivery for the recipients
Alerts reach the same mobile app the workforce already opens for shifts and pay — no separate alerting client to install, no rotted device tokens.
RubyLLM-grounded model tiering
Draft composition and reach prediction route to the right model tier per call — cheap for routine, standard for sensitive sends.
INDUSTRY FIT
Industries where one bad send carries the highest cost
Broadcasts & Alerts Admin Agent helps wherever critical comms have to land fast and right.
Healthcare
Code alerts, weather closures, and patient-safety pages dispatch with audience preview; post-incident summaries satisfy regulatory documentation.
Manufacturing
Plant-floor lockdowns, evacuations, and shift-impacting incidents go out with predicted reach and a clean lifecycle record.
Retail (Multi-Site)
Store-by-store closures, robbery and safety alerts, and weather impacts target the right locations without "all employees" surprises.
Education
Campus-safety alerts and weather closures dispatch with explicit confirmation and an audit-defensible incident summary.
Public Sector
Civic, agency, and field-crew alerts land inside FedRAMP-eligible deployment options with full retention and audit logs.
Logistics & Transportation
Route closures, weather impacts, and depot-level incidents go to the right driver and dispatcher cohorts in one send.
WHY MANGOAPPS WINS
An embedded agent beats a chatbot, a vendor add-on, or a custom build on every axis
The argument finance, security, comms, and ops all share — and the one a single-vendor mass-notification AI structurally cannot answer.
Cheaper than the alternatives
No per-seat ChatGPT license, no Everbridge AI tier, no PagerDuty AIOps upgrade, no six-month custom build, no separate emergency-notification contract.
More secure
All five writes are confirmation-gated. Drafts are draft-only by design. Every action logs to AiApiLog. Alert content stays inside the tenant boundary.
Easier to deploy
Already deployed if you have Broadcasts & Alerts enabled. Turn the admin agent on and the existing audiences and scenarios apply the same day.
Easier to use
Lives inside Ask AI — no separate alerting console, no blank-screen composition mid-incident, no copy-paste between drafting and dispatch.
Easier to manage
Scenario templates, approval routing, and quiet-hours policy all sit in the same admin console as every other app. One audit log, one access model.
Easier to extend
Shares the agentic tool framework with every other MangoApps agent. New scenarios or new approval chains ship as tools, not rewrites.
AI is actually better
A vendor alerting AI can fill in a template. Only the admin agent reads HR scope, scheduling rosters, device-token freshness, and quiet-hours overlap — and gates every dispatch behind explicit confirmation.
At our head office within HR, marketing, and finance, we use ChatGPT quite a bit, and MangoApps AI Helper is a useful tool for us. As I go around to the stores, I’ve been showing them how the AI Intranet Helper can find things and answer plain language questions about our resources, and they’re quite excited about that.
Alison van Zijl
Head of Human Resources
Full House
Customer Success
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Frequently Asked Questions About Broadcasts & Alerts Admin Agent
6 tools — 5 gated writes and 1 read-only summary. compose_alert, compose_broadcast, send_alert_now, cancel_alert, withdraw_alert_approval all require explicit confirmation. summarize_incident is read-only and generates compliance-grade post-incident narratives.
No. All five write tools are in RISKY_TOOLS and gated by user confirmation. compose_alert creates a DRAFT only — sending requires send_alert_now, which surfaces the audience preview, predicted ack curve, and quiet-hours overlap before the admin commits.
compose_alert accepts an optional scenario_template slug (severe_weather_closure, lockdown, IT outage, etc.) that pre-fills body, SMS-shortened text, channels, urgent flag, and ack-required flag from ScenarioTemplateRegistry. Any other arguments the admin passes override the template defaults.
predicted_ack_curve is a read-only forecast based on similar past sends — same audience size band, same channels, same urgency. It returns an expected ack curve plus the number of users likely to be in quiet hours at send time, so the admin can decide whether to bypass quiet hours or delay.
Time-to-draft during incidents, pre-send forecast adoption rate, audience-mismatch incidents (should approach zero), send-to-ack convergence (actual vs predicted), and post-incident documentation time. Compare against your pre-agent baseline.
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