Ensure AI-generated work meets your standards
Rovo creates tickets faster, but missing acceptance criteria, compliance gaps, and AI hallucinations still block delivery. Clarity auto-scores every ticket and prevents low-quality work entering your pipeline, so teams ship with confidence.
Why AI tickets fail in production
Speeding up ticket creation without quality controls creates downstream friction. Clarity closes the gap between AI output and execution-ready work.
- Requirements look complete but hide critical ambiguity
- Acceptance criteria are generic or missing edge cases
- Compliance, audit, or security context is omitted
- Teams discover gaps only after development starts
How Clarity works
Evaluate readiness across summary, description, criteria, and risk context.
Enforce quality gates at workflow transitions before weak tickets enter delivery.
Post in-context guidance and template prompts so teams fix issues fast.
Who It Is For
Teams using Rovo AI to scale ticket creation.
Governance
Organizations enforcing AI quality and compliance standards.
Early Outcome
Lower clarification loops and fewer mid-sprint rewrites.
Execution Signal
Higher confidence that tickets are dev-ready at handoff.
Designed to amplify Rovo, not replace it
Clarity is the governance and quality layer on top of Jira + Rovo workflows. Teams keep using Rovo for ideation and drafting, while Clarity enforces readiness before execution.
- Rovo drafts and summarizes; Clarity validates readiness
- Rovo speeds creation; Clarity prevents weak tickets entering delivery
- Rovo suggests actions; Clarity enforces team-specific quality gates
- Rovo boosts output; Clarity protects sprint predictability
- Together they improve speed and execution quality
Your team’s biggest hidden bottleneck: bad Jira tickets
Poorly defined tickets quietly drain sprint capacity. Clarity is built to stop unclear work before execution begins, where changes are cheapest and team alignment is highest.
- Engineers start with incomplete context
- Requirements are clarified mid-sprint
- Tickets are paused, rewritten, or reopened
- Velocity appears healthy until deadlines slip
- QA validates assumptions instead of requirements
Clarity Value Snapshot
Estimate the value of reducing avoidable clarification and rework once tickets reach In Progress.
Install in JiraHow Clarity stops unclear work before it starts
Built for Jira teams that want to pair AI creation speed with execution discipline. Clarity enforces standards directly in your workflow and creates measurable quality outcomes.
Readiness Control
Ticket Readiness Scoring
Evaluate summary and description quality, flag missing criteria, and score every issue before it enters execution.
See readiness checks →Workflow Governance
Gate Enforcement
Apply quality gates at status transitions so tickets cannot move forward until your definition of ready is satisfied.
See workflow gates →In-Context Guidance
Actionable Feedback in Jira
When a ticket fails checks, Clarity explains exactly what to fix in Jira comments, with templates and autofill to speed remediation.
See issue feedback →Safe and secure by design
Embank Clarity processes ticket content only to evaluate readiness quality and support consistent handoffs across product, engineering, and QA.
- Your Jira tickets are not used to train models
- Region-based processing supports GDPR requirements
- No long-term storage of raw ticket content
- Consistent standards across teams and workflow stages
- Predictable handoffs with shared assumptions
Deploy Clarity as your Jira + Rovo AI / AI readiness layer
Give teams faster ticket creation with Rovo and higher execution quality with Clarity. Book a demo or request early access to install Clarity as a Jira add-on.