Manual drag
Managers chase updates across project tools, chat, documents, timesheets, and standups before reporting.
Delivery/services workflow
AI Project Reportinginside your tools.
Project health, risk flags, status summaries, and client-ready updates appear for manager review.
Built for coos, delivery heads, pmo leaders, and services teams with reporting drag.
Internal proof source: Workstatus + Vinove delivery teams.
KPI moved: Manager hours saved, risk lead time, report turnaround, client update consistency.
01 - Before and after
A painful workflow becomes a governed production path.
Human-approved AI workflow
Status, blockers, delivery signals, and report drafts are assembled with human review and clear ownership.
02 - Route map
Source systems to AI workflow layer to human approval to KPI dashboard.
InputsForms, inboxes, CRM, ERP, project tools, or reporting sources.
AI workflow layerClassification, extraction, enrichment, matching, scoring, or synthesis.
Approval or exceptionHumans approve material actions and review low-confidence cases.
System updateApproved actions are logged back into the agreed system of record.
KPI dashboardBaseline and post-launch KPIs show whether the workflow moved.
03 - What gets designed
The workflow is scoped around systems, approvals, and measurable outcomes.
Systems involved
- Project tool
- Chat
- Docs
- Timesheets
- Client reporting
Approval rules
- Manager approves external updates
- High-risk flags route to delivery leadership
- Missing or conflicting status stays in review
- Client-sensitive language is gated before send
Deployment steps
- Map reporting cadence, source systems, risk signals, and stakeholder needs.
- Connect project, chat, document, and time-tracking sources.
- Build status synthesis, risk flagging, and draft generation.
- Launch with internal reporting first, then client update review.