Control for high-stakes
AI workflows.

DataNXT is designed for finance teams that need governed access, clear data boundaries, traceable outputs, and reviewable workflow steps.

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Security posture

Designed around controlled
financial workflows.

Security is treated as part of the workflow model, not an afterthought.

01

Data boundary options

Support for controlled deployment models and data residency needs, including environments where sensitive information remains within customer-managed infrastructure.

02

Access governance

Role-aware access patterns for teams that need separation between users, workflows, projects, and source collections.

03

Auditability

Workflow steps, source usage, user actions, and generated outputs are designed to be reviewable and attributable.

Governance model

Human review remains part
of the control layer.

DataNXT is structured for teams that want AI support without removing professional judgment from financial work.

Review checkpoints

Define where analysts inspect assumptions, sources, and intermediate results.

Source-level visibility

Keep generated analysis connected to the materials used to produce it.

Information barriers

Designed to support separation of sensitive workflows, teams, and data scopes.

Model governance

Support for controlled AI usage patterns and institution-specific model preferences.

Deployment and operations

Adaptable to institutional
security requirements.

DataNXT is designed to align with the security, compliance, and deployment expectations of financial institutions. Requirements differ across banks, advisors, and investment teams.

Customer-controlled access Data residency options Audit logs Source permissions Information barriers Internal system connectivity

Discuss security requirements during early access.

Join the waitlist to evaluate DataNXT with your team’s governance, data, and deployment requirements in mind.

Request Early Access Explore the Platform