Know exactly how much to
trust your data
UDTR provides a universal standard for rating the trustworthiness of data sources, so organisations can make confident, data-driven decisions without second-guessing their inputs
Universal Data Trust Rating
How it works
A rating you can act on, in three steps
From raw data to an auditable trust score in minutes, not months
Connect your data source
Link any data source, databases, APIs, data lakes, or third-party feeds, through our universal connector layer
Automated trust analysis
UDTR's engine evaluates provenance, completeness, consistency, and freshness across every dimension of your data
Receive your Trust Rating
Get a clear, auditable score from 0–100 with a detailed breakdown so your team knows exactly where to invest confidence
Why it matters
Bad data costs more than
you think
Every decision built on unverified data carries hidden risk. Missed signals, stale sources, and undocumented provenance erode the confidence your team needs to act fast and act right
UDTR gives every data source a score your organisation can stand behind, auditable, consistent, and built on a universal standard that travels across teams, tools, and borders
One number, total clarity
Data modalities
Every kind of data, one universal standard
AI Training Data
Model quality starts with data quality, UDTR rates the provenance, labelling consistency, and representational balance of datasets before they enter your training pipeline, so you know exactly what you are teaching your models
Research Data
Academic and scientific datasets demand rigorous sourcing, UDTR evaluates methodology transparency, peer-review lineage, and reproducibility standards, giving institutions a defensible trust score for every dataset they publish or consume
Commercial & Market Data
Financial signals, pricing feeds, and third-party market datasets carry real business risk when unverified, UDTR applies freshness, coverage, and vendor-reliability checks to give trading and analytics teams a single auditable confidence rating