AI-Powered Deliverables Recommendation via Document Upload or Text Input

Put Simply:
Building on the feature that recommends offerings based on documents or natural language input, this enhancement would go a level deeper—suggesting specific deliverables aligned with the identified needs. By analyzing user-uploaded SOWs, RFPs, or other context, Concourse could surface relevant deliverables to jumpstart or refine the scoping process.

Why It Matters:

• Extends the intelligent scoping journey: Moves from “what to deliver” (offerings) to “how it’s delivered” (actual scoped work).

• Reduces manual effort: Helps users quickly assemble a relevant scope without needing to sift through large templates.

• Improves accuracy and relevance: Ensures that deliverables reflect the specifics of the client’s ask—improving alignment and reducing rework.

What’s Needed:

• AI/NLP model refinement to map parsed content to deliverables, using offering context, building blocks, and PDM metadata.

• UI in the scoping flow to present suggested deliverables alongside offerings.

• User ability to review, accept, or edit the recommendations before adding them to scope.

• Backend support for semantic matching between extracted context and deliverable metadata.