Standard analytics patterns fall short in highly regulated environmnts.

In most analytical systems, execution is transient: a calculation runs, produces an output, and disappears. This works for exploratory workflows, but breaks down when results must be documented, validated, replicated, and reused.

In regulated analytics the calculation itself is a governed object.

A different execution model

In trac, each calculation is defined upfront in an explicit metadata contract that drives execution and is preserved as the record of what was run.

Calculations are auditable, repeatable, and self-documenting.

Used across regulated analytics workflows
Model execution • Scenario analysis • Model risk management • Data pipelines

Explore use cases

What trac is

A governed execution layer for your analytics stack

trac sits alongside your existing tooling — introducing a governed execution layer that connects models, data, and execution into a controlled environment where every calculation is defined, executed, and preserved as a governed object.

Explore deployment options
Description of image

Built in Tier-1 banking environments | Open-sourced via FINOS | Adopted by global systemically important banks

See Finnovate demo

What trac enables

Transforming the regulated analytics operating model

By shifting the unit of control from environments to calculations, trac strengthens controls, improves analytical capability and reduces operational overhead.

The trac runtime can be installed independent of the platform. trac models can be run in your existing tools — from IDEs and notebooks to production environments — and will behave consistently across environments.

Learn more

By defining each calculation as an explicit contract, lineage, explainability and repeatability are intrinsic to execution — not enforced through separate tools or processes.

Learn more

Because every calculation is preserved as a reusable, queryable object, outputs can be combined, compared, and extended without rebuilding pipelines or reconstructing past runs.

Learn more

With execution governed at the calculation level, users can operate more freely - every object is immutable and each run is traceable, reproducible, and controlled.

Learn more

Used across regulated analytics workflows
Model execution • Scenario analysis • Model risk management • Data pipelines

Explore use cases