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Professional Services

Relationship Intelligence Platform in 4 Weeks

Nordic Professional Services Firm · March 15, 2026

Raw Input notes, emails, data Smart Scribe AI auto-structuring Graph Database Contacts Companies Pursuits Contracts Intelligence Agents Dossier, Pathfinder Narrator, War Room BD Insights strategic output Issues Closed 446 PR Merge 10 min AI Agents 5 Delivered In 4 weeks Azure Container Apps + PostgreSQL (Apache AGE)

The Engagement

A Nordic professional services firm needed a bespoke intelligence platform to map and navigate a 20-year relationship network across IT, insurance, finance, and banking. Traditional CRMs forced relationships into linear pipelines — they needed a graph-based system where connections, companies, pursuits, and contracts form a living web of interconnected intelligence. The scope was ambitious: a full-stack production application with graph database modelling, five embedded AI agents, SSO authentication, GDPR-compliant data handling, and Azure cloud deployment — all from a blank repository.

What Was Delivered

The factory delivered the complete platform in 4 weeks with 6 parallel AI workers:

  • Graph-powered relationship engine using PostgreSQL with Apache AGE, modelling contacts, companies, pursuits, and contracts as interconnected nodes and edges
  • 5 embedded AI agents — Smart Scribe (automated data structuring from raw input), Quick Dossier (contact enrichment), Pathfinder (relationship path discovery), Recommendation Narrator (strategic recommendations), War Room (pursuit planning)
  • 20+ application pages including capture workflows, graph visualisation, action tracking, contract management, and an operational dashboard
  • 40+ backend services covering audit logging, deduplication, health scoring, evidence trails, and provenance tracking
  • Microsoft Entra SSO with role-based access control
  • Full Azure deployment on Container Apps with infrastructure-as-code (Bicep), Key Vault, managed PostgreSQL, and CI/CD pipelines
  • GDPR compliance by design — three-layer data architecture separating immutable artifacts, append-only observations, and rebuildable derived views

Results

  • 446 issues closed across the full delivery
  • 483 pull requests merged with a median merge time of 10 minutes
  • 81% of issues resolved within 24 hours
  • 6 parallel AI workers delivering simultaneously
  • 0.6% escalation rate — only 12 of 1,979 work sessions required human intervention
  • 4 weeks from empty repository to production deployment