The problem
Teams that build and change model code re-explain the firm’s documentation and validation-evidence standards to their AI assistant in every session. Documentation drifts away from the code it describes, and model-risk review sends the work back for rework before validation can even start.
How Encephalon addresses it
Encephalon encodes your model-documentation and validation-evidence standards once, so every AI-assisted session produces artifacts in the shape your model-risk function expects. The standard stays current across teams, which keeps two groups from quietly diverging on what “documented” means. One thing to be clear about: this governs the engineering sessions that produce model code and its documentation. Enterprise Intelligence does not monitor or govern a deployed model at runtime, and we will tell you that in the first meeting too.
The outcome
Consistent model documentation that arrives review-ready, a smoother handoff to model-risk management, and less back-and-forth before validation sign-off. SR 26-2 (April 2026) keeps validated models in scope while leaving the AI-assisted work that produces them largely unaddressed, so a defensible record of how model code was built is worth having before your model-risk function asks for it.
Book a 30-minute discovery call with the founding team.