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
Models execute consistently across environments without rework.
Intrinsic governance
Calculations are auditable, repeatable, and self-documenting.
In-situ analytics
Experimental analytics runs safely on production models and data.
These capabilities allow you to:
Eliminate Change Risk
Immutable assets – reproducible calculations.
- Controlled versioning of models and data
- Complete lineage from inputs to outputs
- Fully reproducible historical calculations
- Auditable change and execution history
Accelerate Insight
Rapid and reliable analyis and explaination.
- Safe experimentation on production data
- Iterate from and explore any prior result
- Faster sensitivity and scenario analysis
- Unlock the full power of your infrastructure
Reduce Operating Cost
Eliminate manual controls and fragmented tools
- Simpler deployment and route-to-live
- Automated governance documentation
- Reduced spreadsheet and EUC reliance
- Safe self-service analytics
Where trac sits
A governed execution layer for your existing stack
Use trac to connect your data, compute infrastructure, and developer tools to create a unified environment for building, deploying and running highly regulated models and analytics.
Explore the product![trac architecture](https://images.squarespace-cdn.com/content/v1/66a0cc126cbb6d3bf81f19b7/490fa74f-e89e-4261-be41-2916e8aeb1a3/architecture_partner2.png")
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.
