One operating system for AI governance.
Launchgard brings the AI network, governance workflow and operating controls into one environment — from intake and lifecycle change to reviews, monitoring, issues, audit and reporting.
Tasks
- Approve change CH-042
- Review AI-018 evidence
- Close issue I-203
Network events
- Foundation model updated
- Customer data breach threshold
- Third-party terms changed
Reviews due
- Fraud Triage Model
- Customer Service Agent
- Policy Assistant
Start with what needs attention today.
Workspace gives each team a clear command centre: summary metrics, your tasks, reviews due, active issues, recent network changes and shortcuts to common actions.
Your tasks
- Review GenAI-018
- Approve CH-042
- Close F-182
Needs attention
- Foundation model updated
- Overdue review
- Data threshold breached
Shortcuts
- Register AI
- Start review
- Record issue
See the AI systems and the network around them.
Network combines a structured AI inventory with dependency mapping. Teams can move from a list of systems into the upstream and downstream relationships that shape risk and impact.
Govern AI entering or changing within the network.
Lifecycle tracks new projects, pilots, material changes, approvals and deployment history. It turns AI governance into an operating workflow rather than a static register.
New intake
Scoping
Controls assigned
Material change
Pre-prod review
2 sign-offs left
Approved
Run reviews on the same governance record.
Reviews brings scope, requirements, evidence, findings and decision into one place for initial assurance, periodic review, material change and third-party assessments.
Stay in control after approval.
Monitoring tracks scheduled reviews, ongoing control checks, dependency changes, incidents and signals that may require reassessment or escalation.
Foundation model updated12 dependent systems identified
ReviewData quality threshold breachedUpstream dependency
AssessPeriodic review completedFraud Triage Model
ClosedManage findings and actions in one issue universe.
Issues consolidates findings from reviews, monitoring, audit, incidents and self-identified problems. Each issue is linked to the system, severity, owner and remediation actions.
Support audit of the AI estate.
Audit gives internal audit a structured way to plan work, examine records, test controls and record findings against the same systems, reviews and evidence used by the rest of the organisation.
Turn the estate into management information.
Reports gives leaders portfolio visibility across the AI network — by risk tier, stage, review status, issues, incidents and dependency exposure.
- Customer-facing agents
- Third-party LLM usage
- Overdue periodic reviews
Ask questions across the AI estate.
Ask Launchgard uses the governance graph to answer questions across systems, dependencies, reviews, issues and policies — not just static documents.
2 high-risk systems depend on OpenAI: Customer Service Agent and Policy Assistant. Customer Service Agent has one overdue hallucination review and one open monitoring issue.
Connect systems to policies, standards and evidence.
Library stores the policies, standards, procedures, regulations and supporting documents that define how AI should be governed — and links them to controls, reviews and evidence.
Connect the systems your AI already uses.
Connect is how Launchgard links into the systems used to build, operate and govern AI — so the network stays current and governance records do not become another isolated database.
Bring one AI use case.
See how Launchgard could structure the network, lifecycle, reviews and monitoring around one real AI use case.