Program delivery
North Star
Turn intake documents, team updates, and leadership feedback into an operating plan that stays current.
Internal application
The problem
Delivery leads have to piece together interview notes, process maps, and status updates before they can tell a team what to build or ask leadership for a decision.
Design decisions
I connected intake, delivery, reporting, and artifact creation through one program record. Guided Plans explain which inputs changed the recommendations, while Studio traces its drafts back to source material.
What it does
AI document intake
Analyze statements of work, requirements, status reports, and discovery artifacts to surface scope, stakeholders, risks, decisions, and missing evidence for review.
Living program and role guidance
Use team updates, board activity, and new evidence to refresh program health, phase plans, risks, and next actions for each role.
Reporting and leadership loops
Turn recurring updates into leadership briefs and client-facing reports. Sponsor feedback feeds back into the guidance the team works from.
AI virtual team
Choose a specialist perspective such as product management, business analysis, or UX to get role-specific recommendations and suggested work products.
Admin model controls
Adjust the guidance model, reasoning effort, and response detail. Review usage and audit history, and route disputed guidance for governance review.
AI Artifact Studio
Turn discovery evidence into roadmaps, epics, stories, acceptance criteria, and test cases. Inspect source references, refine saved revisions, and export editable Word, Excel, or PowerPoint deliverables.
Try the workflow
Illustrative example
Turn source material into a program brief
Review scope, risks, and gaps extracted from a statement of work and discovery notes before using them as program context.
Program intake
- Sources
- Statement of work and interview notes
- Outcome
- Make service intake easier to route
- Gap to confirm
- Who owns exceptions?
Screenshot tour
Document intake
Start with a statement of work and discovery notes. The team reviews and corrects the extracted findings before applying them as context for future guidance. The screenshot shows reviewed fields from fictional documents.
How AI helps
One program record, from intake to delivery
North Star uses AI at three points. It analyzes intake and discovery evidence, synthesizes ongoing updates and sponsor feedback into guidance and reporting, and drafts role-specific artifacts in Studio. Teams can inspect which inputs influenced a recommendation or draft.
Example
For a service modernization program, a statement of work establishes scope, a role update flags an unresolved intake decision, and sponsor feedback changes the next action. Studio can use the same evidence to draft stories and tests for review.
What people decide
Teams review the intake findings and can dispute guidance. Admins tune model settings. Reviewers approve specific Studio revisions before handoff, and staff decide what gets published to clients.
Built with
- Next.js
- React
- Postgres
- Vercel
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