One profile across every property in the groupEvery memory traced to its source
);
}
/* ============================================================
* 2B. TWELVE PRIMITIVES
* ============================================================ */
const MEM_PRIMS = [
{ num: "01", kicker: "CAPTURE", title: "Nobody has to type it", body: "Every inbound message, call transcript, email and staff note is read for details worth keeping.", bullets: ["WhatsApp · voice · email · social", "Web chat · PMS · staff notes", "30+ languages, same taxonomy"], quote: "“The detail is saved before the conversation ends.”" },
{ num: "02", kicker: "TAXONOMY", title: "38 typed slots", body: "Not a notes field. Each memory lands in a category agents, segments and journeys already understand.", bullets: ["38 first-class categories", "Custom categories per property", "Typed values, never free text"], quote: "“A notes field is a place details go to die.”" },
{ num: "03", kicker: "PROVENANCE", title: "Traced to the line", body: "Channel, timestamp, message ID and agent are attached to every memory, for ever.", bullets: ["Original message kept", "One click to the source", "Full audit for every edit"], quote: "“Open any memory and see who said it, and when.”" },
{ num: "04", kicker: "CONFIDENCE", title: "Scored, never assumed", body: "A stated fact and a guess are not the same thing, so they never carry the same weight.", bullets: ["Per-memory confidence score", "Low scores held for review", "Stated beats inferred, always"], quote: "“The system knows the difference between told and guessed.”" },
{ num: "05", kicker: "DEDUPLICATION", title: "One truth per fact", body: "The same preference said five times across five channels stays one memory, with five sources.", bullets: ["Merged on capture", "Sources accumulate", "No duplicate clutter"], quote: "“Said five ways, stored once.”" },
{ num: "06", kicker: "INFERENCE", title: "What they never said", body: "Repeat behaviour becomes its own memory, clearly labelled as inferred rather than stated.", bullets: ["Patterns across stays", "Marked as inferred", "Overridden by anything stated"], quote: "“Four stays, same partner. That is worth knowing.”" },
{ num: "07", kicker: "RETRIEVAL", title: "Folded into every reply", body: "Relevant memories are fetched and passed to the agent before a single word is composed.", bullets: ["Ranked by relevance", "Same store on every channel", "No template, no copy-paste"], quote: "“The agent already knew before it answered.”" },
{ num: "08", kicker: "SEGMENTS", title: "Memories as filters", body: "Every category is a queryable field, so audiences are built out of what guests actually told you.", bullets: ["Any category, any operator", "Live counts, recomputed", "Group or single property"], quote: "“Returning pet-parents with an anniversary. One query.”" },
{ num: "09", kicker: "JOURNEYS", title: "Read at send time", body: "Each step re-reads the profile as it sends, so nothing goes out based on a stale snapshot.", bullets: ["Personalised per guest", "Never a frozen merge field", "Steps skip when irrelevant"], quote: "“The email is written the second before it is sent.”" },
{ num: "10", kicker: "HUMAN CONTROL", title: "Edit, pin or forget", body: "Staff correct anything the extractor got wrong, and a forgotten memory disappears everywhere at once.", bullets: ["Inline correction", "Pin the ones that matter", "Forget propagates instantly"], quote: "“The AI proposes. Your team decides.”" },
{ num: "11", kicker: "PRIVACY", title: "Your tenant only", body: "Guest memories stay inside your tenant and are never used to train a shared model.", bullets: ["Isolated per tenant", "No shared-model training", "Deletion honoured end to end"], quote: "“Your guests’ words never leave your walls.”" },
{ num: "12", kicker: "GROUP GRAPH", title: "One guest, every property", body: "Group-level memories follow the guest; property-specific ones stay where they belong.", bullets: ["Group + per-property scope", "Recognised at every hotel", "Scoped memories stay scoped"], quote: "“Known at the second hotel as well as the first.”" },
];
/* Exact per-primitive artwork, transcribed verbatim from the handoff (172×50 viewBox, #ED4D86 -> var(--accent)). */
const PRIM_ART = [
,
,
,
,
,
,
,
,
,
,
,
,
];
function MemoryPrimitives() {
return (
{MEM_PRIMS.map((p, i) => (
{PRIM_ART[i]}
{p.num} · {p.kicker}
{p.title}
{p.body}
{p.bullets.map((b) => (
{b}
))}
{p.quote}
))}
);
}
/* ============================================================
* 2. RETRIEVAL AT RUNTIME
* ============================================================ */
const MEM_PILL_POOL = [
["Special date", "Anniversary · May 14"], ["Pet", "Frankie · 8 kg"], ["Dietary", "Partner vegetarian"], ["Stay pref", "High floor"],
["Loyalty tier", "Gold · 2022"], ["Allergy", "Shellfish"], ["Bed setup", "Twin beds"], ["Family", "With mother"],
["Check-in", "After 22:00"], ["Climate", "AC off"], ["Drinks", "Sancerre"], ["Quiet room", "Away from lobby"],
["Trip purpose", "Anniversary trip"], ["Communication", "WhatsApp first"], ["Last stay", "Suite 412"], ["Spend pattern", "Spa most stays"],
["Companion", "Same partner"], ["Mood", "Wants quiet"], ["Open issue", "Spa noise · Mar"], ["Resolved", "Breakfast credit"],
["Sensitive note", "Fragrance"], ["Brand affinity", "3 properties"], ["Likely return", "May–June"], ["Restaurant", "La Terraza"],
["Floor", "Sea view side"], ["Pet", "Bed + bowl"], ["Dietary", "No red meat"], ["Special date", "Birthday · Sep 2"],
["Stay pref", "Early housekeeping"], ["Drinks", "No ice in water"],
];
const MEM_RETRIEVAL_EXAMPLES = [
{
channel: "WhatsApp",
question: "Hi, can we book the same room as last time?",
answer: "Welcome back, Mr. Mitsopoulos. Suite 412 is free 14–17 May and I have held it for you.",
hits: [
{ cat: "Last stay", v: "Suite 412 · 14–17 Mar 2025", src: "PMS note" },
{ cat: "Stay pref", v: "High floor, sea view", src: "Inferred" },
],
lit: [3, 14],
},
{
channel: "Voice",
question: "We would like a table for our anniversary dinner.",
answer: "Booked for the 14th at 20:30, with the vegetarian tasting menu noted for your partner.",
hits: [
{ cat: "Special date", v: "Anniversary · 14 May", src: "Voice" },
{ cat: "Dietary", v: "Partner vegetarian", src: "Email" },
],
lit: [0, 8],
},
{
channel: "Email",
question: "Anything we should confirm before we arrive?",
answer: "Frankie’s bed is already in the room, and we have kept you on the quiet side, away from the lobby.",
hits: [
{ cat: "Pet", v: "Dachshund · Frankie · 8 kg", src: "WhatsApp" },
{ cat: "Quiet room", v: "Away from lobby", src: "Email" },
],
lit: [5, 19],
},
{
channel: "Web chat",
question: "Is the kitchen able to handle allergies?",
answer: "Your severe shellfish allergy is already flagged with every kitchen in the hotel, including room service.",
hits: [
{ cat: "Allergy", v: "Shellfish · severe", src: "WhatsApp" },
{ cat: "Restaurant", v: "Always books La Terraza", src: "Inferred" },
],
lit: [11, 23],
},
];
const MEM_RETRIEVAL_STEPS = ["Identify the guest", "Fetch memories", "Rank by relevance", "Compose the reply"];
const CHANNEL_ICON = {
WhatsApp: ,
Voice: ,
Email: ,
"Web chat": ,
};
function MemoryRetrievalDemo() {
const [idx, setIdx] = useStateMem(0);
const [phase, setPhase] = useStateMem("asking");
const [qTyped, setQTyped] = useStateMem(0);
const [aTyped, setATyped] = useStateMem(0);
const [scanned, setScanned] = useStateMem(0);
const timers = useRefMem([]);
useEffectMem(() => {
let alive = true;
const schedule = (fn, ms) => { const id = setTimeout(() => { if (alive) fn(); }, ms); timers.current.push(id); return id; };
const ex = MEM_RETRIEVAL_EXAMPLES[idx];
let scanInt;
setPhase("asking"); setQTyped(0); setATyped(0); setScanned(0);
let qi = 0;
const qInt = setInterval(() => {
qi = Math.min(ex.question.length, qi + 2);
setQTyped(qi);
if (qi >= ex.question.length) {
clearInterval(qInt);
schedule(() => {
setPhase("searching");
scanInt = setInterval(() => setScanned((s) => Math.min(47, s + 3)), 45);
}, 400);
schedule(() => {
clearInterval(scanInt);
setScanned(47);
setPhase("matched");
schedule(() => {
setPhase("answered");
let ai = 0;
const aInt = setInterval(() => {
ai = Math.min(ex.answer.length, ai + 2);
setATyped(ai);
if (ai >= ex.answer.length) clearInterval(aInt);
}, 18);
}, 700);
}, 1300);
}
}, 24);
schedule(() => setIdx((i) => (i + 1) % MEM_RETRIEVAL_EXAMPLES.length), 4600 + 1300 + 950);
return () => { alive = false; clearInterval(qInt); clearInterval(scanInt); timers.current.forEach(clearTimeout); timers.current = []; };
}, [idx]);
const ex = MEM_RETRIEVAL_EXAMPLES[idx];
const activeStep = phase === "asking" ? 0 : phase === "searching" ? 1 : phase === "matched" ? 2 : 3;
const rShowResult = phase === "matched" || phase === "answered";
const rShowAnswer = phase === "answered";
const rSearching = phase === "searching";
const stepData = [
{ label: "Identify the guest", done: "Matched to profile #84412", active: "Resolving number → profile", pending: "Awaiting contact" },
{ label: "Fetch memories", done: "Whole profile loaded", active: `${scanned} of 47 read`, pending: "Awaiting profile" },
{ label: "Rank by relevance", done: `${ex.hits.length} memories selected`, active: "Scoring against the question", pending: "Awaiting memories" },
{ label: "Compose the reply", done: `Sent on ${ex.channel}`, active: "Writing with memories in context", pending: "Awaiting selection" },
];
const rStatus = phase === "asking" ? "Waiting for the guest"
: phase === "searching" ? `${scanned} of 47 memories read`
: phase === "matched" ? `${ex.hits.length} relevant memories selected`
: "Reply composed with memory in context";
return (
<>
{/* Responsive-only overrides: this component is otherwise entirely
inline-styled (see memory-styles.jsx header). Below ~760px the
two-pane layout can't hold its 42% conversation pane + fixed
760px height without clipping, so it stacks instead. */}
{/* LEFT: guest-side conversation */}
{CHANNEL_ICON[ex.channel]}Guest · via {ex.channel}
Being asked the same question a third time is the moment a loyal guest becomes a transaction. Memory is the difference between a hotel that recognises someone and a system that processes them.
One profile · every property · every channel · every agent
);
}
/* ============================================================
* 3. LIVE TAGGING (TAXONOMY)
* ============================================================ */
const MEM_TAG_COLS = [
{ name: "Identity & lifecycle", color: "var(--accent)", seed: [["FAMILY", "Travelling with mother"], ["LOYALTY TIER", "Gold · since 2022"]] },
{ name: "Stay preferences", color: "#4f9d8f", seed: [["PILLOW", "Firm · two of"], ["CHECK-IN TIME", "Late · post 22:00"]] },
{ name: "Dining & dietary", color: "#5b6bb0", seed: [["ALLERGY", "Shellfish · severe"], ["RESTAURANT", "Books La Terraza"]] },
{ name: "Behaviour & context", color: "#c06a4f", seed: [["MOOD", "Wants quiet, decompressing"], ["TRIP PURPOSE", "Wedding anniversary"]] },
{ name: "Issues & resolution", color: "#8a6a9c", seed: [["RESOLVED", "Breakfast credit given"], ["SENSITIVE NOTE", "Housekeeping fragrance"]] },
{ name: "Inferred", color: "#b8843c", seed: [["LIKELY RETURN", "May–June window"], ["COMPANION", "Same partner · 4 stays"]] },
];
const MEM_TAG_SCENARIOS = [
{ src: "WhatsApp · inbound", pre: "Hello again! We’ll be back May 14–17, our ", hi: "anniversary", post: ". Same suite if possible", col: 0, chip: "SPECIAL DATE", val: "Anniversary · May 14" },
{ src: "WhatsApp · inbound", pre: "Same suite if possible? ", hi: "Frankie", post: " is coming, hope that’s still ok", col: 0, chip: "PET", val: "Dachshund · Frankie" },
{ src: "Email · inbound", pre: "One thing to flag: ", hi: "my partner doesn’t eat meat", post: ", is that easy for you?", col: 2, chip: "DIETARY", val: "Partner vegetarian" },
{ src: "Voice · transcript", pre: "Could we have ", hi: "twin beds", post: " this time, my mother is joining", col: 1, chip: "BED SETUP", val: "Twin beds · second guest" },
{ src: "Web chat", pre: "Last time the spa music was ", hi: "far too loud", post: " in the afternoon", col: 4, chip: "OPEN ISSUE", val: "Spa noise · Mar stay" },
{ src: "Voice · transcript", pre: "We ", hi: "always", post: " do the tasting menu when we come", col: 3, chip: "SPEND PATTERN", val: "Books tasting menu most stays" },
{ src: "No message", pre: "Fourth stay booked with the same companion", hi: "", post: "", col: 5, chip: "COMPANION", val: "Same partner · 4 stays", noQuote: true },
{ src: "WhatsApp · inbound", pre: "Could you put us on a ", hi: "high floor", post: ", sea side if there is one?", col: 1, chip: "FLOOR", val: "High floor, sea view" },
];
function MemoryTaggingDemo() {
const [scIdx, setScIdx] = useStateMem(0);
const [phase, setPhase] = useStateMem("reading");
const [placed, setPlaced] = useStateMem(() => MEM_TAG_COLS.map((c) => c.seed.map(([chip, val]) => ({ chip, val, fresh: false }))));
const timers = useRefMem([]);
useEffectMem(() => {
let alive = true;
const schedule = (fn, ms) => { const id = setTimeout(() => { if (alive) fn(); }, ms); timers.current.push(id); return id; };
setPhase("reading");
schedule(() => setPhase("sorting"), 1200);
schedule(() => {
const sc = MEM_TAG_SCENARIOS[scIdx];
setPlaced((prev) => {
const next = prev.map((col) => col.map((x) => ({ ...x, fresh: false })));
const key = sc.chip + "|" + sc.val;
next[sc.col] = [{ chip: sc.chip, val: sc.val, fresh: true }, ...next[sc.col].filter((x) => x.chip + "|" + x.val !== key)].slice(0, 3);
return next;
});
setPhase("placed");
}, 2200);
schedule(() => setScIdx((i) => (i + 1) % MEM_TAG_SCENARIOS.length), 4300);
return () => { alive = false; timers.current.forEach(clearTimeout); timers.current = []; };
}, [scIdx]);
const sc = MEM_TAG_SCENARIOS[scIdx];
const hiOn = phase === "sorting" || phase === "placed";
const sorting = phase === "sorting";
return (
<>
{/* Responsive-only overrides: this component is otherwise entirely
inline-styled (see memory-styles.jsx header). The 3x2 category
grid and its fixed 660px shell height don't fit a phone-width
container, so the grid drops to 1 column and the shell height
becomes content-driven below ~700px. */}
Profile #84412 · 6 stays across 3 properties · last seen on WhatsApp today. Memories are shared across the group; property-scoped memories stay with their hotel.
Add memory
{[["MEMORIES", "47", "on this profile"], ["CATEGORIES", "19", "of 38 in use"], ["SOURCES", "5", "channels contributing"], ["EDITED BY STAFF", "3", "corrections kept"]].map(([k, v, s], i) => (
0 ? "1px solid rgba(20,20,20,0.07)" : "none" }}>
{k}
{v}
{s}
))}
Filter
AllStatedInferredStaff-addedSorted by last updated
{MEM_PROV_SEED.map((r, i) => {
const open = i === openRowIdx && rowRank >= 1;
const rc = memCatColor(r.cat);
return (
This memory lives in your tenant only. It is never used to train a shared model, and forgetting it removes it from every agent, segment and journey immediately.