DRM for AI
Know what is feeding your AI models — and prove it is under control.
Data Risk Monitor extends data lineage to AI, tracing every data set, feed and upstream model that contributes to a model's output, and showing where accuracy, completeness and timeliness risks are introduced and ensuring AI compensates...
The challenge
AI models rarely stand alone
The models a firm relies on draw on internal data, third-party feeds and, increasingly, the outputs of other AI models — chained together across a pipeline that is rarely visible end-to-end.
When accuracy, completeness or relevance breaks down, it surfaces downstream as a flawed output, often with no clear trace back to the cause. Yet boards are now expected to stand behind those outputs.
How DRM helps
A live map from source to model output
DRM maps the full journey of data into a model — from source, through every transformation, to the point it reaches the model. At each step it identifies where risks are introduced and how they could propagate to the output.
Where an upstream model is itself a source of risk, through its own data quality or drift, that risk is captured and traced through too — giving you a live, evidence-based picture to build controls on, not static documentation that dates the moment it is written.
Key benefits
01
Transparency at every level
See how the AI models you rely on are fed with data, in a form that can be understood from data teams to the board.
02
Demonstrable AI controls
Evidence that controls are in place over the data feeding your models, as AI regulation comes into force.
03
A risk control framework
Identify the risks to your models and plan, capture and monitor the controls that mitigate them.
The regulatory picture
Evidencing control over model data is becoming a baseline expectation
European Union
EU AI Act obligations for high-risk systems phase in through 2026 and 2027, including data governance requirements.
South Korea
The AI Basic Act is already in effect.
China
Binding AI-specific rules have been introduced.
UK & US
Each is moving in its own direction, with regulators expecting firms to understand and govern their models.
Who it is for
Board & senior management
Stand behind model outputs with confidence.
Model risk
Assess and control risk at the model.
Data teams
Trace every input and its quality.
Compliance
Evidence for AI regulation, on demand.
See what is really feeding your models
Talk to us about mapping the data behind your AI.
