Research

Evidence that can be examined, not marketing labelled as research.

This hub documents how KloudGentic develops methods and, when enough genuine work exists, publishes aggregated findings about AI-built product readiness and SME workflows. We do not publish invented studies, percentages, or representative claims without a defined sample.

Latest research

No public dataset or benchmark report is currently published. The planned SME Workflow Index and State of AI-Built Apps report will remain unpublished until the sample and permissions are sufficient.

Methodologies

AI-built App Audit methodology
Workflow Blueprint: current process, frequency, handling time, exceptions, automation suitability, remaining human review, cost, and validation period.

Data and benchmarks

Public aggregates will state sample size, collection period, measurement definitions, limitations, and anonymisation approach. Customer-identifying data will not be published without express approval.

Research notes

Short research notes will identify whether a statement is a primary-source fact, KloudGentic measurement, approved customer evidence, or professional judgement.

Evidence policy

A — Primary external source: regulators, official documentation, government data, standards, or filings.
B — KloudGentic measured evidence: defined sample, method, period, and limitations.
C — Customer evidence: approval, attribution where possible, actual status, and measured data when published.
D — KloudGentic judgement: clearly framed as experience or recommendation, never converted into an invented statistic.

How evidence is collected and anonymised

Operational observations are recorded using consistent fields. Public reporting uses aggregates or redaction appropriate to the consent and sensitivity of the work. Project status is not presented as an outcome, estimates are labelled, and internal ventures are distinguished from customer engagements.