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Conseil.dev
[AI_SECURITY]

AI automation without exposing client data

Conseil.dev designs AI workflows for regulated, privacy-conscious teams that need control over data access, residency, review, auditability, and deployment choices.

Confidentiality is part of the workflow

We define what data the system can access, who can see outputs, what needs human approval, and how activity should be logged before a pilot goes live.

[CONTROLS]

Security notes for production AI

Every AI workflow should make data exposure, access, and review decisions explicit.

No training on client data

Model and vendor choices are reviewed against the client's data handling requirements.

Private and open-source options

Workflows can run on private, on-premises, or open-source infrastructure to limit vendor lock-in and keep sensitive data in your control.

Canadian data residency

Where it matters, data and workloads stay under Canadian jurisdiction instead of foreign-controlled platforms.

Role-based access

Users only see the documents, answers, and actions their role should permit.

Audit trails

Important actions can be logged so teams understand what happened and when.

Source citations

Private knowledge workflows should show where answers came from, not just produce text.

Human approval workflows

Sensitive steps are prepared by AI and approved by a person before they leave the system.

NDA-first approach

Confidential projects start with clear handling expectations before discovery begins.

[REGULATED_TEAMS]

Built for legal, accounting, finance, healthcare operations, and private knowledge workflows

The goal is not a generic chatbot. The goal is a controlled system that helps staff move faster while preserving review, access boundaries, and evidence.

Need to prove the security model before building?

Use the AI Adoption Roadmap to document privacy risks, data readiness, access rules, and the pilot architecture before implementation.