Workspace Overviews
Summarize the permitted reporting scope within the current operating workspace.
Workspace OverviewsSummarize the permitted reporting scope within the current operating workspace.
Record AssistanceAsk for contextual guidance while inspecting a service or operational record.
Retrieval ContextGround assistance in scoped graph and vector retrieval before model fallback.
Confidence SignalsIdentify ungrounded or low-confidence guidance before relying on it.
RetrieveExplain
Use workspace and record assistance with scoped retrieval, visible source evidence and confidence indicators.
What Connects Here
Explore in detailRecord Assistance
Ask for contextual guidance while inspecting a service or operational record.
Retrieval Context
Ground assistance in scoped graph and vector retrieval before model fallback.
Confidence Signals
Identify ungrounded or low-confidence guidance before relying on it.
Retrieve → Explain → Review
Explore the details below, then bring your workflow, source data and questions to a guided conversation.
Built into the platform
The capabilities behind
the experience.
Workspace overviews
Summarize the permitted reporting scope within the current operating workspace.
Record assistance
Ask for contextual guidance while inspecting a service or operational record.
Retrieval context
Ground assistance in scoped graph and vector retrieval before model fallback.
Confidence signals
Identify ungrounded or low-confidence guidance before relying on it.
Human review
Keep recommendations separate from approval, customer publication and physical execution.
AI control plane
Administer the AI configuration and review platform usage context.
Actual product view
Inside AI & Assistance.
See the running demo environment. Features and records are subject to your role, configuration and integrations.
Connected by design
Context travels
with the work.
Service records, configuration items, people, locations and evidence share the same operational foundation. Move from investigation to the related asset, service or customer workflow with clear ownership.
Explore the platform architectureImplementation context
Features depend on enabled modules, configured roles, source data and supported integrations. Agree your implementation scope and acceptance criteria during discovery.
Who this is for
AI governance leads, platform administrators, service architects and operational reviewers
AI adoption creates governance gaps when a generated overview is mistaken for an approved action. Evaluators need to understand permitted retrieval, confidence, evidence and the human control points surrounding operational decisions. An evaluation of AI & Assistance should make those boundaries inspectable before the team relies on the operating view.
Illustrative walkthrough
Review assistance as part of the operating control model
A fictional governance team evaluates an AI overview in a restricted workspace and record assistance on a service issue. It checks grounding and insufficient-evidence behavior before agreeing which human roles may use the guidance in their operating process.
01Establish scoped retrieval
Identify the permitted reporting scope and inspect the graph or vector context available to assistance before discussing how the generated overview should be used. Summarize the permitted reporting scope within the current operating workspace.
02Review uncertainty and sources
Ask for the evidence behind the guidance and demonstrate how ungrounded or low-confidence output is surfaced to the user reviewing the response. Ground assistance in scoped graph and vector retrieval before model fallback.
03Retain the human control point
Use the AI control plane and operational process to distinguish assistance from change approval, customer publication or physical execution responsibilities. Keep recommendations separate from approval, customer publication and physical execution.
Review one useful response and one insufficient-evidence response with the accountable operational owner, then document the approval boundary that remains outside the recommendation itself. Use demonstration records and preserve the applicable reporting scope.
Explore the platform
See Qintorava in action.
Open a workspace for a closer look.
Prepare the evaluation
Bring the right inputs.
What to prepare
- Scoped retrieval and record context
- AI configuration and usage view
- Human review and escalation responsibilities
Candidate measures to agree
- Responses reviewed with source context
- Uncertain outputs escalated appropriately
- Operational decisions retaining accountable reviewers
These are evaluation criteria, not promised outcomes. Agree the baseline, scope, source coverage and acceptance method with the responsible owners before drawing conclusions.
Questions for this topic
Get the details.
Does assistance automatically authorize an operation?
No. Recommendations remain separate from approval, publication and physical execution, and the responsible role should inspect evidence and prerequisites before using guidance in an operational decision.
What happens when confidence is low?
Confidence indicators help users identify weak or ungrounded guidance; reviewers should seek additional evidence or human escalation rather than treat a fluent answer as verified operational fact.
How is customer data treated for training?
Qintorava states that real customer data is not used for training and only demo data is used; the applicable customer agreement should define deployment-specific data processing obligations.
Your next operating chapter
See what connects
when everything connects.
Bring one workflow, one service challenge or one part of your estate. We’ll show you where Qintorava fits.