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Revinate Ivy (AI decision-intelligence layer)

door Revinate

AI Application
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Ivy is Revinate's decision-intelligence layer across its whole platform. Today it powers Chat (guest-facing AI concierge), automated scoring of every reservation call in real time (conversion opportunities and coaching moments), AI-written campaign content and segment-specific copy, sentiment analysis of reviews and surveys with suggested review responses, AI-driven identity resolution and data-quality checks in the CDP, and an 'agentic interface' exposing guest intelligence to customers' AI agents and other tools. Roadmap items include predictive insights, strategic campaign execution (creating segments, writing content, choosing channels and timing within guardrails), proactive occupancy monitoring and a continuous learning loop. It profiles individual guests at very large scale (the vendor cites 1.1 to 1.25 billion profiles across 12,500+ hotels) to decide who to target, with what offer, on which channel. Rated medium. Revinate claims SOC 2 Type II, GDPR, CCPA and PCI-DSS compliance, an isolated tenant, that all recommendations need customer approval, and that it never uses PII to train models without consent, but these were not verified (Trust Center and DPA unreadable). Key open points: Ivy 'learns' from behavioral data across all customers after identity is stripped ('synthetic data layer'), so de-identified guest data appears to be used for model learning by default, with no stated de-identification standard, consent mechanism or opt-out; the 'approval before execution' claim does not fit automatic outputs such as Chat replies, and the roadmap includes autonomous campaign execution; call scoring involves analyzing recorded calls and may be used to assess individual agents, with consent and retention not described; the 'agentic interface' exposes guest data to external AI agents with no stated access controls; model providers are not named; and no accuracy figures are published beyond an absolute claim that Ivy does not hallucinate. The rating would rise if the de-identification is not true anonymization, there is no opt-out, or agentic campaign execution goes live without approval gates.

Bezoek website

Transparantiescore

Gewogen over vier pijlers · bijgewerkt October 16, 2026

Totaalscore
27% gewogen
ABCDF
Model
—
Nog niet beoordeeld
Infrastructuur
—
Nog niet beoordeeld

Functionaliteiten

Guest Level Personalization And Targeting
Automated Reservation Call Scoring
Ai Marketing Content Generation
Sentiment Analysis And Review Response Suggestions
Ai Identity Resolution And Data Quality
Agentic Interface For External Ai Agents

Leveranciersinformatie

Volledige informatie over de leverancier/provider van deze AI-applicatie

RevinateBekijk alle producten →
Revinate, LLC(Handelsnaam: Revinate)
Contactinformatie
www.revinate.com/
info@revinate.com
+1 415-671-4703
Geregistreerd adres
543 NW York Drive, #120, Bend, OR, 97703, US

Leveranciersinformatie volgens de EU AI Act

Verificatiestatus:
Unverified
(Laatst geverifieerd: October 15, 2026)
Revinate, LLC(Handelsnaam: Revinate)
543 NW York Drive, #120, Bend, OR, 97703, US
info@revinate.com+1 415-671-4703
The Trust Center (Vanta) is the stated source for security documentation, product terms and privacy practices, but its content could not be read. The vendor says it offers 24/7/365 support, 45 to 90 days typical implementation for a first property, and controls to turn off specific Ivy functionality. No public status page, incident history or AI incident process was found in the pages read.
The vendor says Ivy 'doesn't' hallucinate because it uses hospitality-specific data, an absolute claim with no published accuracy, error or escalation metrics. It says all recommendations require customer approval, but Chat answers guests automatically (up to 80%) without per-message approval. Statistics differ across pages (1.1 billion versus 1.25 billion guest profiles). The agentic features (strategic campaign execution) are roadmap items, not current capabilities.

Potentiële risico's

1 aandachtspunten geïdentificeerd

1

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Deze aandachtspunten worden automatisch geïdentificeerd op basis van openbaar beschikbare informatie over de leverancier en AI-catalogusgegevens. Werkelijke risico's kunnen variëren afhankelijk van uw specifieke use case en implementatie.

Naleving & risico

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Toegevoegd: October 16, 2026
Bijgewerkt: October 16, 2026

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