Founding Engineer & Technical Lead
Vexor
An AI-powered legal case-management platform that converts incoming notifications into structured triage decisions.
- Initial delivery
- 2-3 months
- Team growth
- +2 engineers
- Integration
- Galaxy CRM
01 · Context
The system behind the product
Took the product from concept to a stable production system for a European legal firm group, then expanded the engineering team.
02 · Architecture
How the system is shaped
- 01
Incoming legal notifications enter a Python processing pipeline that extracts structured case information and applies scenario-aware triage logic.
- 02
The AI decision layer publishes comments and triage outcomes into Galaxy CRM so legal teams stay inside their existing operating workflow.
- 03
Azure Container Apps and private endpoints provide an isolated production boundary for application and integration services.
03 · Decisions
Trade-offs made explicit
Integrate where work already happens
AI output is surfaced inside Galaxy CRM instead of forcing legal users into a second disconnected interface.
Structure before automation
Notification content is normalized into explicit case data before scenario rules and LLM-assisted decisions are applied.
Scale the team after the spine worked
The initial production system established the core boundaries before two additional Python engineers were onboarded.
04 · Outcome
What changed
Delivered the initial production platform in 2-3 months and integrated its AI decisions directly into the client's existing CRM workflow.
- Moved from concept to a stable production system in 2-3 months.
- Reduced workflow fragmentation by placing generated case comments and triage decisions directly in the client's CRM.
- Expanded delivery capacity with two additional Python developers while retaining architectural and client ownership.
05 · Capabilities
What the work involved
- Legal document processing
- AI decision pipelines
- CRM integration
- Team formation