Portfolio maturity: Working Prototype · Explainable Executive Proposal Intelligence
Think Through Seven Executive Brains. Build Better Proposals.
C-SUITE7 AI is an executive proposal-intelligence and quality-coaching platform. It is not a proposal-writing AI — it evaluates a proposal package for completeness, quality and readiness against a corporate executive benchmark, so the team consistently ships more complete, persuasive and professionally structured proposals.
A clean four-step intake flow:
- Organization Information — who the client is, the project, the objective.
- Magic Box — paste any links or notes (Drive, Docs, Canva, YouTube,
WhatsApp, NotebookLM, meeting minutes…). Stored in
Links.md. - Upload Center — drag & drop proposals, decks, posters, budgets. Files are auto-sorted into the correct folders.
- Executive Assessment — a 100-point quality score, the Executive 7-Lens Benchmark (CIO, CFO, CTO, COO, CSO, CRO, CMO), strengths, weaknesses, missing items and a prioritised Top-10 improvement list.
Every submission is saved to Google Drive as a numbered folder
(P018 - XYZ Enterprise) with the standard structure:
P018 - XYZ Enterprise
├── 01 Organization
├── 02 Proposal
├── 03 References/Links.md
├── 04 Executive Analysis
│ ├── ExecutiveAssessment.md
│ ├── ProposalScore.md
│ ├── ImprovementChecklist.md
│ └── ExecutiveSummary.md
└── README.md
The next proposal number is determined automatically from existing folders.
The interface is available in four languages, switchable from the header
(preference saved to localStorage):
- English
- Bahasa Melayu
- 华语 · Mandarin
- Jaku Iban (best-effort — worth a native-speaker review)
All static UI is localised (src/lib/i18n). The dynamically generated
assessment prose (per-category coaching notes, lens recommendations, executive
summary) is produced by the engine in English; the category names, lens roles
and band labels around it are localised.
Next.js (App Router) · React · TypeScript · TailwindCSS. No database. No auth (V1). Google Drive is the storage backend.
npm install
cp .env.example .env.local # optional — runs with defaults
npm run devOpen http://localhost:3000.
The app ships with a local filesystem backend so it runs with zero setup
(files land in ./.data/). To use Google Drive:
STORAGE_PROVIDER=drive
DRIVE_MASTER_FOLDER_ID=YOUR_APPROVED_FOLDER_ID
GOOGLE_SERVICE_ACCOUNT_KEY={...service-account JSON...}The service account must have Editor access to the master folder.
The codebase is deliberately layered so future modules plug in without a refactor:
| Layer | Location | Responsibility |
|---|---|---|
| UI / wizard | src/components/wizard |
Four-step intake |
| Result UI | src/components/assessment |
Score & lens display |
| Assessment engine | src/lib/assessment |
Deterministic, explainable scoring |
| Storage | src/lib/storage |
StorageProvider interface + Drive/local adapters |
| Orchestration | src/lib/proposal.ts |
Ties submission → assess → persist |
| API | src/app/api |
submit, next-number routes |
The assessment engine is rule-based and transparent — every score is explainable, which is exactly what a coaching tool needs.
The structure anticipates (without building) AI proposal rewriting, proposal
comparison, a gallery, version control, cross-team benchmarking, dashboard
analytics, approval workflows, client feedback, templates and knowledge-base
integration. Add them as new lib modules and routes — the storage and
assessment layers are already decoupled.
Status: Working Prototype — an explainable, rule-based executive proposal-intelligence platform. It is suitable for demonstrations and structured internal evaluation, but every assessment requires human review.
Product strategy, assessment workflow and solution direction are led by Zaiwin Kassim, together with the KOBIS AI Prodigy Team, using supervised AI-assisted development.
Production use requires authentication, organisation-approved storage, least-privilege Drive access, privacy controls, retention rules and human review of every assessment.