Trust, security & governance

Trust & Governance

Practical safeguards for AI-assisted work in regulated financial institutions.

Our approach

Trust is built into the workflow

Regulated work requires more than an accurate output. It requires accountable decisions, evidence that can be inspected, and clear controls around how AI is used.

MultiplAI is designed to make review faster while keeping people, evidence, and governance at the centre of the process.

01

Human accountability

MultiplAI supports analysts rather than replacing their judgment. Users review, approve, correct, or dismiss AI-assisted findings before final submission.

  • Human review remains part of the decision workflow
  • Findings can be corrected, approved, or dismissed
  • Reviewer actions remain visible in the audit record
02

Evidence and traceability

Answers remain connected to their source material so reviewers can verify what the system found and preserve the evidence behind each decision.

  • Source-linked answers support efficient verification
  • Actions and decisions are time-stamped
  • Review evidence can be retained in an auditable record
03

AI governance

MultiplAI is designed for controlled use in regulated workflows, with an emphasis on grounded outputs, visible uncertainty, and clear escalation to human reviewers.

  • Outputs are designed to remain grounded in source evidence
  • Exceptions and uncertainty are surfaced for review
  • AI assists the process without owning the final decision
04

Access and operational security

MultiplAI uses access controls and separated operational environments to help protect institutional workflows and maintain visibility into platform activity.

  • Role-based access aligns platform permissions with user responsibilities
  • Audit logs provide visibility into user actions and system activity
  • Development and production environments are separated
Data handling

Institutional data stays protected and controlled

Customer data is not used to train shared AI models. Data is encrypted in transit and at rest, and retention policies can be configured according to institutional requirements.

Evaluating MultiplAI for your institution?

Talk with our team about your governance, data-handling, and deployment requirements.