- Ratecard Summary: Total Hours column now uses =SUM() formulas
- Grand total row uses =SUM() formulas per column
- New "Assumptions & Rates" sheet with editable inputs:
- Global: Hours per FTE, Margin %, Overhead %
- Per-role: Day Rate (£), Annual Salary (£)
- Yellow highlighted input cells for Finance to edit
- Foundation for full formula-linked financial model
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Ratecard Summary caveats row now combines AI match caveats with the
original GMAL asset caveats (labelled "GMAL Standard Caveats:") below.
Asset Detail sheet splits these into two separate columns.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Inserts an "Assumptions / Caveats" row (row 2) in the Ratecard Summary
sheet so users can see each asset's AI-matched caveats without switching
to the Asset Detail tab. Uses the same amber colour scheme as the PDF report.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Efficiency preview: toggle 10/25/50/75/90% to see adjusted FTE live
- Programme roles NOT reduced (they don't scale with AI)
- Excel export: select multiple efficiency levels, each gets its own tab
showing original vs adjusted hours/FTE/headcount with hours saved
- Export buttons on both Ratecard and Team Shape tabs
- team_shape service accepts efficiency_pct parameter
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- Team shape service: total_hours / 1800 = FTE per role
- Programme roles (6) flagged separately from delivery roles
- New API endpoint GET /projects/{id}/team-shape
- Team Shape tab in frontend with summary stats and role breakdown
- Sheet 3 "Team Shape" in Excel export with discipline grouping,
delivery vs programme split, FTE, rounded headcount, and summary
- Full GMAL catalog matching (replaced pre-filter with compact catalog)
- Upload progress stages with live polling
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Dockerized web app (FastAPI + React + PostgreSQL) for scoping client ratecards
against the GMAL master asset database. Features:
- GMAL data ingestion from Excel (390 assets, 120 roles, 5 model types)
- AI-powered document parsing and asset extraction (Claude Opus 4.6)
- AI matching engine with parallel batching, confidence scoring, caveats
- Ratecard builder with hours x volume calculation
- Excel and PDF export
- GMAL browser and inline editor
- AI cost tracking per project (persisted to DB)
- Debug panel for AI call inspection
- Dark theme UI with gold (#FFC407) accent
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
