Synthesize
Bring related signals into a concise review narrative.
Atlas AI
Investigate the Azure estate through grounded product context.
AI assistance is useful when evidence, boundaries, and review remain visible.
Ask operational questions, synthesize available context, and draft next steps while keeping write-class actions in separate governed paths.
- Operational questions
- Context synthesis
- Drafted follow-up
- Separate action controls
Atlas AI assists operators; it can be incomplete or wrong and its output requires review. Available grounding, model routing, data handling, and advanced action controls depend on the configured customer environment.
Ask with context
Operating practiceBegin with an operating question, not an unbounded prompt.
Atlas AI is designed around questions such as what changed, why cost moved, what risk affects a resource, or what should enter a review pack. A defined tenant, scope, and period improves the usefulness of the investigation.
- 01
Question
State the decision or uncertainty the operator needs to resolve.
- 02
Scope
Keep tenant, estate boundary, and time window explicit.
- 03
Review
Validate the answer against available product and source evidence.
Product evidence
Implemented capabilityWork across synchronized Lineage surfaces.
Atlas AI can use available Lineage context from resources, history, cost, risk, activity, recommendations, and workflow records. Coverage is bounded by configured sources, permissions, sync freshness, and the tools available to the session.
- Estate and resource context
- Historical and cross-domain review context
- Workflow and report preparation context
Human review
Implemented capabilityUse the answer as analysis material, not automatic authority.
Atlas AI can summarize evidence, organize hypotheses, and draft review notes or next-step material. Operators remain responsible for validating facts, source freshness, calculations, and recommendations before decisions are recorded.
Draft
Prepare follow-up questions, action notes, or report material.
Validate
Check material claims against the relevant source surfaces.
Governed operations
Implemented capabilityA conversation is not permission to change Azure.
Write-class operations are separate from ordinary Atlas analysis. Where Azure Write or Deployment Mode is enabled, configured identity, Azure RBAC, product permissions, policy checks, approval, execution records, and verification apply.
- No implied authorization from a chat request
- Separate approval and execution path
- Configuration and environment determine availability
Known limits
Operating practiceTreat freshness, completeness, and model error as operating concerns.
Reviewers should inspect sync state, confirm source coverage, avoid placing unsupported secrets in prompts, and validate consequential outputs. Account-specific controls and data handling should be reviewed before broader use.
- 01
Freshness
Check whether relevant data is current, stale, failed, or still synchronizing.
- 02
Completeness
Identify missing sources and permissions before drawing conclusions.
- 03
Accuracy
Require human review for decisions and consequential actions.
Service and advisory
Service and advisoryReview model, data, and action architecture per environment.
Swaves can support use-case framing, evaluation criteria, model-routing review, permission design, and operating controls. No public claim is made here about a customer-specific model, residency outcome, or deployment topology.
- Define high-value questions and acceptance tests
- Review data flow, model routing, and access boundaries
- Separate investigation rollout from advanced action enablement
Evaluate Lineage
Evaluate Atlas AI on a bounded investigation.
Choose the evidence, question, and acceptance criteria before assessing answer quality or action scope.