Marketplace/Asset #1704LISTED

AI data asset · anonymous listing

#1704

ZendeskJiraLinearGitHub
AI Data Asset Score5 interested parties
67/100
Potential data value
Assessment available after diligence
Licensing readiness
REVIEW REQUIRED
Preferred structure
Non-exclusive license with de-identified sample first
Data room

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

Data overviewListed 2026-01-22
Industry
SaaS
Region
Nordics
Company size
500–2,000 employees
Years operating
27+
Historical data
12 years
Estimated records
310,000+ records
ERP
NetSuite
CRM
Salesforce
Approx. employees
890
Data types3 categories
  • Support Tickets
  • Engineering Workflows
  • Case Management
Workflow familiesDepth: excellent
  • Tier-1 to tier-3 escalation
  • Incident command and postmortem
  • Change review
  • Implementation milestone tracking

Cross-system connectivity

Zendesk → Jira → Linear

Score composition67 / 100

Volume

310,000+ records in scope.

61

weight 12

Historical depth

12 continuous years of operating history.

59

weight 12

Workflow complexity

Multi-step decisions with real exception handling.

64

weight 12

Cross-system connectivity

Records join across 4 systems on shared keys.

52

weight 11

Uniqueness

SaaS operational reasoning is scarce in open corpora.

66

weight 10

Data quality

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

86

weight 9

Outcome labels

Outcomes are recoverable from downstream records.

79

weight 9

Industry value

Active buyer demand for saas agents.

76

weight 8

AI-agent relevance

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

80

weight 8

Licensing readiness

Customer MSAs restrict disclosure of ticket content.

54

weight 5

Privacy / de-identification complexity

Customer environment details in tickets.

70

weight 4

Why this asset scored 67

This saas asset covers 12 years of tier-1 to tier-3 escalation and related decisions across Zendesk, Jira, Linear. 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
  • Support deflection
  • Evaluation benchmarks
  • Vertical AI agents
Data rights & provenanceNot a legal determination

Ownership

Company-generated operational records in owned tenants.

READY

Source systems

Zendesk, Jira, Linear, GitHub.

READY

Third-party data

Vendor support threads.

REVIEW REQUIRED

Customer / client data

Customer environment details in tickets.

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

Customer MSAs restrict disclosure of ticket content.

REVIEW REQUIRED

Licensing permissions

Pending rights review.

NOT VERIFIED

Retention period

12 years retained; no scheduled destruction.

READY

Geographic restrictions

EU transfer mechanism required.

REVIEW REQUIRED

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
MODERATE
Historical depth
LOW
Workflow complexity
MODERATE
Cross-system connectivity
LOW
Industry uniqueness
MODERATE
Data quality
HIGH
Outcome labels
MODERATE
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.