property-match

johannes.gasser/property-match

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Author	SHA1	Message	Date
Benjamin Sutter	efc406ace9	feat: role-aware UX, market intelligence, score fix & layout scroll - Role-based workspace access: Property Manager gets Supply+Demand, Operations restricted to Super Admin + Reviewer only - Root redirect routes each persona to their first workspace - Match Center: replaced 3-panel with auto-sorted flat list + drawer - AI Search: unified form with dual-action (Jetzt suchen / Als Suchprofil speichern) - CompareTray hidden on non-Demand routes; Vergleichen removed from Supply - LocationIntelligencePanel: city KPIs, rent trends, soft factors, comparables - NegotiationInsightsPanel: price positioning, active demand, selling arguments - scoreCalculator: cap hardMatchScore and softFactorScore to max 100 - Layout: add display:flex to overflow:hidden wrappers so inner scroll works (MatchCenter drawer, MarketIntelligence, SourceMonitoring, SignalPipeline) Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>	2026-05-17 00:58:10 +02:00
Benjamin Sutter	3152de004c	feat: F009 matching engine V1 — deterministic multi-criteria scoring domain/scoring.ts: HARD_FILTER thresholds, DATA_QUALITY/CONFIDENCE modifier tables, ScoringWeightProfile type, DEFAULT_SCORING_PROFILES for Office/Retail/Light Industrial/Logistics/Production/Default (all sum to 1.00), HARD/SOFT_CRITERION_KEYS, MatchEngineOutput type. features/matching/scoreCalculator.ts: applyHardFilters (asset type mismatch, area < 85% min, budget > 150%, excluded region → hard exclude; occupied → severe penalty), scoreArea/Location/Budget/Timing as ScoreFactor, scoreSoftFactor for 9 keys mapped to property.softFactors, calcDataQualityModifier/calcConfidenceModifier, calculateScore (resolves profile from need.weightingProfile + default, runs filters, computes normalized hard/soft scores, applies modifiers, classifies positive/negative factors, assembles MatchEngineOutput). features/matching/tradeOffAnalyzer.ts: analyzeTradeOffs (6 patterns: location-vs-budget, area-vs-budget, timing-vs-dataQuality, prestige-vs-flexibility, futureSignal-vs-location, accessibility-vs-commute), analyzeRisks (future signal, data quality, budget, occupied, low confidence, missing critical fields), identifyMissingData (rentPricePerSqm, availabilityDate, softFactors, hardFacts, need.budgetRange). features/matching/rankingEngine.ts: matchStrengthFromScore (>=78 STRONG, >=52 MODERATE, else WEAK), generateNextBestActions (score-based, future signal SCHEDULE, missing data VERIFY), buildFullMatch → full Match entity with ScoreBreakdown + explainabilitySummary + uncertaintyIndicators, rankMatches (score desc → resultType order → confidence desc), computeRankedMatches batch helper. services/matchService.ts: computeMatch(need, property) and computeMatchesForNeed(needId) wired to engine. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>	2026-05-16 12:54:45 +02:00

Author

SHA1

Message

Date

Benjamin Sutter

efc406ace9

feat: role-aware UX, market intelligence, score fix & layout scroll

- Role-based workspace access: Property Manager gets Supply+Demand,
  Operations restricted to Super Admin + Reviewer only
- Root redirect routes each persona to their first workspace
- Match Center: replaced 3-panel with auto-sorted flat list + drawer
- AI Search: unified form with dual-action (Jetzt suchen / Als Suchprofil speichern)
- CompareTray hidden on non-Demand routes; Vergleichen removed from Supply
- LocationIntelligencePanel: city KPIs, rent trends, soft factors, comparables
- NegotiationInsightsPanel: price positioning, active demand, selling arguments
- scoreCalculator: cap hardMatchScore and softFactorScore to max 100
- Layout: add display:flex to overflow:hidden wrappers so inner scroll works
  (MatchCenter drawer, MarketIntelligence, SourceMonitoring, SignalPipeline)

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

2026-05-17 00:58:10 +02:00

Benjamin Sutter

3152de004c

feat: F009 matching engine V1 — deterministic multi-criteria scoring

domain/scoring.ts: HARD_FILTER thresholds, DATA_QUALITY/CONFIDENCE modifier tables, ScoringWeightProfile type, DEFAULT_SCORING_PROFILES for Office/Retail/Light Industrial/Logistics/Production/Default (all sum to 1.00), HARD/SOFT_CRITERION_KEYS, MatchEngineOutput type.

features/matching/scoreCalculator.ts: applyHardFilters (asset type mismatch, area < 85% min, budget > 150%, excluded region → hard exclude; occupied → severe penalty), scoreArea/Location/Budget/Timing as ScoreFactor, scoreSoftFactor for 9 keys mapped to property.softFactors, calcDataQualityModifier/calcConfidenceModifier, calculateScore (resolves profile from need.weightingProfile + default, runs filters, computes normalized hard/soft scores, applies modifiers, classifies positive/negative factors, assembles MatchEngineOutput).

features/matching/tradeOffAnalyzer.ts: analyzeTradeOffs (6 patterns: location-vs-budget, area-vs-budget, timing-vs-dataQuality, prestige-vs-flexibility, futureSignal-vs-location, accessibility-vs-commute), analyzeRisks (future signal, data quality, budget, occupied, low confidence, missing critical fields), identifyMissingData (rentPricePerSqm, availabilityDate, softFactors, hardFacts, need.budgetRange).

features/matching/rankingEngine.ts: matchStrengthFromScore (>=78 STRONG, >=52 MODERATE, else WEAK), generateNextBestActions (score-based, future signal SCHEDULE, missing data VERIFY), buildFullMatch → full Match entity with ScoreBreakdown + explainabilitySummary + uncertaintyIndicators, rankMatches (score desc → resultType order → confidence desc), computeRankedMatches batch helper.

services/matchService.ts: computeMatch(need, property) and computeMatchesForNeed(needId) wired to engine.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

2026-05-16 12:54:45 +02:00

2 Commits