Iterative Prompting:
- Chat box on Match Review tab for natural language refinement
- "re-run under 70%" / "ignore zero volume" / "set all volumes to 1"
- Claude interprets instruction into structured actions
- Actions: rematch_below_threshold, rematch_specific, delete_assets, set_volume
- Re-matches affected assets automatically after refinement
- Chat log shows instruction history
RFP/Brief Analysis:
- New "Brief Analysis" tab between Upload and Match Review
- Extracts: summary, objectives, KPIs, channels, audiences, deliverable categories,
constraints, timeline, budget, complexity assessment
- Generates prioritized discovery questions (Red/Amber/Green)
- Questions include category, rationale, and priority level
- Stored as JSON in project.brief_analysis field
- Uploaded files now saved to data dir for re-analysis
- Re-analyze button to refresh analysis
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- Team Shape tab: profile selector (Conservative/Moderate/Aggressive)
- BTG tool toggles (Pencil, OMG, Creative X, Cortex, Semblance, Share of Model)
- Per-discipline rates shown inline with combined profile+tool percentages
- Efficiency % column in table showing rate per role
- Flat rate fallback still available (10/25/50/75/90%)
- Match feedback endpoint: POST /matches/{id}/feedback (confirm/reject)
- Feedback learning: confirmed matches stored, checked before AI calls
- Known matches applied instantly (no API call, $0 cost)
- Remaining unknowns sent to Claude as before
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Assets with quantity 0 are meaningless downstream (produce 0 ratecard hours)
and clutter the review stage — filter them out at parse time.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Move AI parsing and matching into BackgroundTasks so both endpoints
return immediately instead of blocking until Claude finishes (~60s+)
- Frontend now polls project status after upload/match POST returns,
keeping the spinner/progress UI working as before
- Replace <a href> export links with programmatic Axios downloads to fix
missing /gsb base path and missing auth token (401 in production)
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>
- New ai_descriptions service: generates rich brief-friendly descriptions
per GMAL asset via Claude, grouped by category (135/243 generated)
- Descriptions include client synonyms, inclusions/exclusions, use cases,
channel/format info, complexity differentiators
- GMAL Browser shows AI descriptions with green/amber status indicators
- GMAL Editor: editable AI descriptions, per-asset regenerate, batch generate all
- Matching catalog now includes AI descriptions for better semantic matching
- Fixed ORM session expiry bug: snapshot asset data before batch commits
- Fixed enum issue: removed unused UPLOADING/EXTRACTING statuses
- Added app-level logging (basicConfig) so service logs show in docker
- YOLO now batches 20 selections in parallel
- Matching returns 1 best match by default, extras only within 5% of top
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>
- Upload now shows live stage progress (uploading -> extracting -> AI parsing -> done)
- Fix match group collapse: proper React state instead of DOM manipulation
- Replace pre-filter with full GMAL catalog sent to Claude (~3k tokens, <$0.01)
- FTS and keyword matching missed too many semantic matches
- Claude now sees all 243 assets and uses semantic understanding
- Improved system prompt with terminology bridges for better scoring
- Per-project AI cost tracking persisted to DB
- Parallel matching with cancel support
- Auto-select matches >= 80%, YOLO button for rest
- Debug panel for AI call inspection
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>
