Marketplace/Asset #1899UNDER NDA

AI data asset · anonymous listing

#1899

Opera PMSToastWorkdayMicrosoft 365
AI Data Asset Score3 interested parties
69/100
Potential data value
Assessment available after diligence
Licensing readiness
REVIEW REQUIRED
Preferred structure
Time-limited pilot, renewable on outcome
Data room

Seller identity is never disclosed at this stage. Introduction requires buyer qualification, seller approval and executed confidentiality.

Data overviewListed 2026-07-24
Industry
Hospitality
Region
United States
Company size
100–500 employees
Years operating
29+
Historical data
4 years
Estimated records
42,000+ records
ERP
Workday
CRM
HubSpot
Approx. employees
260
Data types4 categories
  • Schedules
  • Financial Records
  • Invoices
  • Customer Relationships
Workflow familiesDepth: excellent
  • Rate and inventory decisions
  • Labour scheduling under demand shifts
  • Guest recovery handling
  • Supplier ordering

Cross-system connectivity

Opera PMS → Toast → Workday

Score composition69 / 100

Volume

42,000+ records in scope.

45

weight 12

Historical depth

4 continuous years of operating history.

67

weight 12

Workflow complexity

Multi-step decisions with real exception handling.

68

weight 12

Cross-system connectivity

Records join across 4 systems on shared keys.

74

weight 11

Uniqueness

Hospitality operational reasoning is scarce in open corpora.

76

weight 10

Data quality

Structured fields are strong; free-text completeness varies by year.

73

weight 9

Outcome labels

Outcomes are recoverable from downstream records.

85

weight 9

Industry value

Active buyer demand for hospitality agents.

66

weight 8

AI-agent relevance

Tool-using, multi-system workflows suit agent training and evaluation.

90

weight 8

Licensing readiness

Brand franchise agreements require review.

56

weight 5

Privacy / de-identification complexity

Guest reservation details.

62

weight 4

Why this asset scored 69

This hospitality asset covers 4 years of rate and inventory decisions and related decisions across Opera PMS, Toast, Workday. Scarcity is the strongest factor: this class of operational reasoning is largely absent from public corpora. The score is held back by de-identification work on party identifiers and uneven free-text completeness in earlier years.

Potential AI applications
  • Vertical AI agents
  • Scheduling
  • Support deflection
Data rights & provenanceNot a legal determination

Ownership

Company-generated operational records in owned tenants.

READY

Source systems

Opera PMS, Toast, Workday, Microsoft 365.

READY

Third-party data

OTA channel records.

REVIEW REQUIRED

Customer / client data

Guest reservation details.

REVIEW REQUIRED

Employee data

Approver identities appear in workflow audit trails.

REVIEW REQUIRED

Potential PII

Names and work contact details appear in free text.

REVIEW REQUIRED

Contract restrictions

Brand franchise agreements require review.

REVIEW REQUIRED

Licensing permissions

Pending rights review.

NOT VERIFIED

Retention period

4 years retained; no scheduled destruction.

READY

Geographic restrictions

United States operations only.

READY

Intended AI use

Seller prefers training plus evaluation, no resale.

REVIEW REQUIRED

De-identification requirements

Entity and person pseudonymisation required pre-sample.

REVIEW REQUIRED

Status indicators reflect seller-reported information and SentryRights screening only. No asset is represented as legally licensable until rights and privacy diligence is completed with the seller and, where applicable, its counsel.

Demo data — illustrative sample listings, not live marketplace records

Data readiness
Volume
LOW
Historical depth
MODERATE
Workflow complexity
MODERATE
Cross-system connectivity
MODERATE
Industry uniqueness
MODERATE
Data quality
MODERATE
Outcome labels
HIGH
PII risk
MODERATE
De-identification difficulty
MODERATE
Licensing readiness
REVIEW REQUIRED
Introduction process
  1. 1

    Buyer submits request

    Identity, funding stage and entity are verified before the request moves.

  2. 2

    Buyer provides intended use

    Specific model, application and downstream distribution limits stated in writing.

  3. 3

    Platform reviews buyer

    SentryRights qualifies the buyer and screens the intended use against seller preferences.

  4. 4

    Seller receives request

    Seller sees the buyer profile and intended use while remaining anonymous.

  5. 5

    Seller approves or declines

    No identity is disclosed without an explicit seller approval.

  6. 6

    NDA / confidentiality

    Mutual confidentiality executed through the platform.

  7. 7

    Identity revealed

    Counterparties are introduced only at this point.

  8. 8

    Data diligence begins

    Rights review, privacy review and de-identification are coordinated by SentryRights.