Coenties

Useful intelligence.
Deliberate control.

Every workflow has its own operating context. These are the design principles we propose to evaluate with your business, engineering, and risk teams.

Only what the workflow needs.

Define approved sources, permissions, data retention, and model-provider data handling before connecting a system. Deployment choices depend on the client’s requirements and available infrastructure.

Keep evidence close.

Where the workflow produces document-based claims, include source references and make missing or ambiguous information visible to the reviewer.

Make approval explicit.

Identify which actions require review. Financial advice, underwriting, investment, lending, and other consequential decisions remain with the appropriate client personnel.

Test beyond the happy path.

Use representative cases, including incomplete inputs and exceptions. Measure output quality, rework, failure behavior, and task completion against agreed criteria.

Know who owns the next step.

Scope monitoring, escalation, incident response, rollback, and support responsibilities. Agree on how changes to prompts, models, rules, and integrations are reviewed.

Define the actual commitment.

Document architecture, ownership, and delivery responsibilities for each engagement. This page describes a proposed approach; it does not claim certifications, universal compliance, or features already deployed for customers.

Discuss your
AI workflow requirements.

An introductory call to discuss your operational priorities, existing systems, and potential scope of engagement.

Discuss your requirements

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