Concourse & Jira DC Portal

Simply Put

Enable Solution Architects to generate high-quality, first-draft content for the early stages of the solution plan using AI — reducing manual effort, improving consistency, and accelerating pursuit timelines.

Problem / Pain Point

Solution Architects face recurring pain points when creating the Solution Architecture layer, including manually building diagrams from scratch due to the lack of reusable templates or a centralized repository. There's no standard visual framework or integration with delivery tools like E-Pro or Concourse, leading to inconsistencies and disconnected planning.

High Level Requirements

1. Modular GPT or AI Agent Design

   • Generated by a dedicated module with clear logic.

   • Outputs should be editable and exportable (e.g., into slides, Jira, Concourse).

2. Prompt Flow

   • Defined prompt structures (e.g., “Given this RFP, generate a vision statement with industry relevance”).

   • Customizable for practices/areas .

3. Structured Outputs

   • Content should be returned in structured formats that can be easily modified into diagrams.

4. Search & Reuse Templates

   • AI must surface relevant past examples from a tagged knowledge repository (e.g., similar industries, offerings, clients).

   • Embedded recommendations for similar pursuit assets (like “gold standard” decks).

5. User Controls

   • Allow for refinement, regeneration, or modular editing of outputs.

   • Support for tailoring based multiple practices/needs

Key Inputs

• RFP or Proposal Request: Source document used to extract themes, scope, and goals.

• Client Info: Industry, geography, public filings (e.g., 10-K), size, maturity.

• Pursuit Metadata: Opportunity type, offering, team roles, size, client tier.

• Prebuilt Templates: Benefit frameworks from LEAP and Benchmarking.

• Past Pursuits / Proposals: Structured examples tagged by offering, industry, and plan layer.

Expected Outputs

• Business Capabilities to Benefits Layer: Graphic that shows capabilities, benefits, KPIs, and specifics to a solution (if known).

Metrics

• Tool Utilization: Frequency of tool use per user.

• Output Engagement: Number of times suggestions are copied or downloaded.

• User Satisfaction: Percentage of positive user ratings (e.g., thumbs up, satisfaction scale) for AI-generated results.

• Efficiency Improvement: Reported reduction in time required to generate output slides.
  
  
  Notes/Quotes:
  -“Architecture lives in a slide — it’s disconnected from the rest of the plan.” — Sanjyoth Paracha