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frontend: label machine-generated output and unbuilt entitlements (Gate A)
Gate A (BUSINESS_MODEL.md, board minutes #42, dated to today by minutes #79
decision 14) blocks putting a price or an unbuilt entitlement claim on a
surface a reader can see, and requires that unverified machine assertions be
labelled as such on the same screen as the assertion.

The pricing leg was already met — /pricing and both homepage CTAs stopped
quoting the invented catalog. Condition A2 was not: a search of the whole
frontend for a "machine-generated" or "unverified" qualifier returned zero
hits. Every transcript, summary, title, location, unit list and vehicle list
is pipeline output that no human reviews, and entity-name accuracy in those
transcripts has never been measured (server-26#48) — yet all of it was
rendered to the reader as plain fact. Unqualified machine assertions about
real incidents and real people is the exposure Gate A exists to stop.

A2 — one reusable element, components/ui/MachineOutputNotice.tsx, rendered on
the same screen as the output (a footnote elsewhere does not satisfy A1's
"same screen" standard). Three variants for three shapes of surface, all
saying the same thing; the "popup" variant uses fixed grays because a Leaflet
popup is stock-white in both themes. Covered:

  - incident detail: under the summary (covers summary, title, location,
    units on scene/cleared, vehicles, tags) and above the call spine
  - incident list: above the timeline groups
  - Archive (/calls): above the transcript rows
  - node detail: above the Recent Calls table
  - Watch//alerts: above the events table, whose Snippet column is transcript
    text and whose keyword match was made against it
  - Live map: the desktop incident rail, pinned above the scroll area so it
    cannot be scrolled off the screen it qualifies; the mobile drawer; the
    incident marker popup; the incident-path stop popup
  - /systems: the source-call transcript preview
  - /features: the two marketing sections that describe the AI pipeline

A1 — components/ui/UnbuiltMarker.tsx marks a claim unbuilt inline:

  - /faq: the retention answer promised 7/90/365-day windows. There is no TTL
    and no deletion sweep anywhere in the product (server-26#44), so the
    answer now states plainly that nothing is deleted automatically and marks
    per-plan retention as not yet available.
  - /settings/billing: the plan cards' claims — custom retention, SSO/SAML,
    uptime SLA, data residency — are marked not-yet-available next to the plan
    that makes them.

Labelling only. No retention, SSO, SLA or residency was built; no billing,
Stripe or checkout code was touched (Gate B still bars charging anyone); no
price was added anywhere; no Python was touched. Both themes verified against
the light-mode !important overrides in globals.css, which are untouched.

tsc --noEmit clean.

Refs: server-26#46, server-26#44, server-26#48

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
2026-08-31 02:47:40 -04:00

119 lines
5.1 KiB
TypeScript

import { Card } from "@/components/ui/Card";
import { Badge } from "@/components/ui/Badge";
import { LinkButton } from "@/components/ui/Button";
import { MachineOutputNotice } from "@/components/ui/MachineOutputNotice";
const SECTIONS: {
eyebrow: string;
title: string;
body: string;
points: string[];
/** Section describes AI pipeline output — render the Gate A / A2 qualifier. */
qualify?: boolean;
}[] = [
{
eyebrow: "Correlation",
title: "Calls become incidents",
body:
"The correlation engine groups related transmissions — across talkgroups and even across nodes — into a single incident. A pursuit renders as a path through every checkin point heard while it moved; a structure fire or accident renders as a pin at the location dispatch gave.",
points: [
"Hybrid rule + LLM correlation with a cheap/smart consensus tiebreak",
"Distance, timing, shared units, and talkgroup signals all feed the match",
"Every call keeps its correlation debug trail for admins to audit",
],
qualify: true,
},
{
eyebrow: "AI pipeline",
title: "Transcription and entity extraction",
body:
"Every recorded call is transcribed and scanned for the details that matter — units on scene, vehicles, and locations — so an incident reads like a dispatch briefing instead of a stack of raw audio.",
points: [
"Automatic speech-to-text on every call",
"Scene & entity extraction feeds the correlator and the incident summary",
"AI-generated incident summaries, regenerable on demand",
],
qualify: true,
},
{
eyebrow: "Situational awareness",
title: "Live map, full history",
body:
"Glance at the map to see what's active right now, or scrub back through history to review how a specific incident unfolded — every linked call, in order, with playback.",
points: [
"Real-time node and incident map",
"Per-incident call timeline with audio playback",
"Configurable alert rules that post to Discord on keyword or talkgroup match",
],
},
{
eyebrow: "Field hardware",
title: "Field SDR nodes",
body:
"Lightweight edge nodes run OP25/GNU Radio against a P25 or analog trunked system and stream decoded audio to your account. Deploy one node to cover a town, or a whole network across a region.",
points: [
"P25 and analog trunked systems supported",
"Per-node hardware tuning (gain, PPM, antenna) persists independently of system assignment",
"Node health, call activity, and configuration all visible from the dashboard",
],
},
{
eyebrow: "Team",
title: "Discord voice relay & role-scoped access",
body:
"The Discord bot relays live radio audio into a voice channel so your team can listen along without a separate app, and doubles as a lightweight utility bot for team coordination.",
points: [
"Live audio relay per node, on demand",
"Admin / operator / viewer roles, with operators scoped to the nodes they own",
"Discord account linking for in-Discord commands",
],
},
];
export default function FeaturesPage() {
return (
<div className="max-w-screen-xl mx-auto px-4 md:px-6 py-16 md:py-20">
<div className="max-w-2xl">
<Badge tone="brand">Features</Badge>
<h1 className="text-display-sm md:text-display text-white mt-5">Everything between the radio and the map</h1>
<p className="text-gray-400 mt-4 leading-relaxed">
DRB is the pipeline from decoded radio traffic to a picture your team can act on: transcription,
correlation, mapping, and a live relay — end to end.
</p>
</div>
<div className="mt-16 space-y-16">
{SECTIONS.map((s) => (
<div key={s.title} className="grid grid-cols-1 lg:grid-cols-5 gap-8 items-start">
<div className="lg:col-span-2">
<p className="text-indigo-400 text-xs font-mono uppercase tracking-wider font-semibold">{s.eyebrow}</p>
<h2 className="text-white text-2xl font-bold mt-2">{s.title}</h2>
<p className="text-gray-400 mt-3 leading-relaxed">{s.body}</p>
</div>
<Card padding="lg" className="lg:col-span-3">
<ul className="space-y-3">
{s.points.map((p) => (
<li key={p} className="flex items-start gap-3 text-sm text-gray-300">
<span className="mt-1.5 w-1.5 h-1.5 rounded-full bg-indigo-500 shrink-0" />
{p}
</li>
))}
</ul>
{/* Gate A / A2 (server-26#46) — the sections that describe the AI
pipeline carry the same qualifier the product surfaces do. */}
{s.qualify && <MachineOutputNotice className="mt-5" />}
</Card>
</div>
))}
</div>
<div className="text-center mt-20 pt-16 border-t border-gray-800">
<h2 className="text-display-sm text-white">See it running on your own traffic</h2>
<div className="mt-6">
<LinkButton href="/login" size="lg">Get started</LinkButton>
</div>
</div>
</div>
);
}