Controlled analytics for regulated environments
A governed exection layer that works with your existing stack — making calculations auditable, repeatable, and self-documenting.
A new execution model for regulated analytics
Every calculation is defined, executed and recorded as a single governed unit.
Portable execution
Execute models consistently across environments without rework.
Intrinsic governance
Embedding lineage and repeatability through contract-based execution.
In-situ analytics
Run, monitor and evolve analytics directly on production models and data.
These capabilities allow you to:
Eliminate Change Risk
Immutable models and data – fully traceable, reproducible calculations.
- Complete lineage from inputs to outputs
- Fully reproducible historical calculations
- Controlled versioning of models and data
- Auditable change and execution history
Accelerate Insight
Deploy, iterate, and explain results without delay.
- Safe experimentation on production data
- Analyse and explore any prior result
- Faster sensitivity and scenario analysis
- Unlock the full power of your infrastructure
Reduce Operating Cost
Eliminate manual controls, fragmented tooling and duplicate processes
- Simpler deployment and route-to-live
- Automated governance documentation
- Reduced spreadsheet and EUC reliance
- More self-service analytics
What trac is
A governed execution layer for your existing stack
Connect your data and compute infrastructure and developer tools using trac to create a controlled environment for building, deploying and running models.
Explore architecture
Where trac adds value
Where governed execution matters most
For your most critical and highly governed analytics — including capital, liquidity and provisioning — trac ensures that every calculation is auditable, repeatable and self-documenting.
Combining the flexibility of a desktop tool with the control of an enterprise platform, TRAC allows you to recreate any prior run, vary assumptions and compare outcomes safely and quickly.
From ongoing model monitoring to independent validation, trac lets you manage libraries of statistical tests alongside model assets and run them safely against production models and data.
