Mortgage AI Governance
Move Mortgage AI Into Production With Control and Proof
Crittora adds a control and evidence layer to the governance, security, and compliance systems mortgage organizations already use. It is designed to help approved AI actions proceed, stop actions outside the rules, and preserve evidence of what occurred.
The control + evidence layer for mortgage AI.
AI request
Core system
Authority boundary
Decision
Proceed / stop
Evidence
Actor / action / result
The execution gap
Governance cannot stop at the policy.
The moment AI takes action is where policy becomes consequence. Crittora is designed to make that moment controllable, reviewable, and provable.
01
Know
Know which system or agent is acting, what it is attempting, and under whose authority.
02
Stop
Stop actions that fall outside approved rules before they reach a consequential system.
03
Prove
Retain defensible evidence of the decision, the action, and the resulting state.
AI Governance in a Box
Put governance into operation—without replacing the stack you trust.
Crittora sits between mortgage applications and core systems, applying the authority defined by your program and preserving evidence for the teams that oversee it.
01 / Existing environment
Integrate without disruption
Designed to sit between mortgage applications and core systems while supporting established SIEM, logging, GRC, audit, and governance processes.
02 / Configurable governance
Adapt as requirements evolve
Template authority rules, evidence mappings, and review outputs to the client’s workflows, applicable frameworks, and evolving requirements.
03 / Evidence output
Produce audit-ready proof
Preserve tamper-evident records of authorized AI actions and route client-specific evidence into established audit and compliance review processes.
See the control and evidence layer in action.
Schedule a demoOne layer.
Three paths.
A shared control point for the mortgage AI ecosystem.
01
Mortgage enterprises
Make consequential AI workflows controllable and reviewable across governance, security, risk, compliance, and technology teams.
02
Mortgage consultancies
Add an execution-control and evidence capability to client governance, compliance, security, and implementation engagements.
03
Technology platforms + AI builders
Give customers a clearer control point between an AI-enabled product and the systems where consequential state changes occur.
A simple start.
One workflow. One clear authority perimeter.
The first engagement is designed to turn an abstract governance concern into a concrete operating model.
01
Frame
Select one consequential workflow and define the operational decision that matters.
02
Bound
Identify the actors, actions, systems, and limits that form the authority perimeter.
03
Prove
Specify the evidence reviewers need to understand the decision, action, and result.
04
Expand
Use what is learned to decide where the control and evidence pattern should go next.
Control is only half the answer
Turn operational evidence into a defensible review record.
Crittora is designed to preserve tamper-evident evidence of the authority decision, the requested action, and what occurred. Evidence outputs and framework mappings can be configured to the client’s workflow, applicable requirements, and review process.
Evidence Packs are client-specific deliverables scoped during an engagement. They support audit and compliance review; they do not certify compliance or guarantee an outcome.
Governance evidence pack
Workflow review record
Review copy
Actor
Identified
Authority
Scoped
Decision
Recorded
Action
Bounded
Result
Captured
Evidence
Retained
Client-specific mapping • Applicable framework • Workflow controls • Reviewer requirements
For technical teams
A stack-agnostic control pattern. A bounded place to begin.
Crittora is currently AWS-based. Supported system integrations, logging destinations, evidence outputs, and deployment patterns are confirmed during technical evaluation.
Questions before production
What enterprise teams ask first.
Begin with the action that matters
Find the authority gap before AI finds it for you.
Bring one consequential mortgage workflow. We will frame the actors, actions, authority limits, and evidence needs that shape a practical first evaluation.