Problem
Founders often start with broad ideas but no repeatable way to turn an industry choice into a realistic plan, staffing model, income assumptions, or startup sequence.
Project case study
NAICS Startup Planning System
Software that guides founders through structured startup planning workflows instead of vague brainstorming.
Project facts
Theme
Operational Workflow Software
Current state
Prototype
My role
Sole architect and full-stack engineer
Core constraint
Explainability: every generated recommendation must trace back to a rule, data source, or constraint, not a black-box model
Outcome
Working planning engine with rules-based role generation, income modeling, and explainability views across NAICS hierarchy
Approach
A concise problem → system → evidence structure so the engineering story is easier to inspect.
System design
Built as an offline-first planning engine backed by the full NAICS hierarchy. The system combines rules-based role generation, income modeling, dependency-ordered startup procedures, and explainability views so users can inspect why each recommendation was produced.
Rules engine converts industry data into launch-plan structure.
Explainability layers make the output inspectable rather than magical.
Offline-first runtime keeps the system usable without external APIs.
Stack
Next.jsPrismaSQLiteZodRules EngineSnapshot Tests
Evidence
The planning engine is supported by a documented rules architecture and outputs that show the provenance of each recommendation.
Planning engine diagramRules traceGenerated plan artifacts
Related work
Projects in a similar problem family.
Operational Workflow SoftwareBeta Pilot
DealerFlow
Vehicle monitoring and notification platform that aggregates inventory updates and alerts users to relevant deals.
My Role
Sole backend engineer and mobile developer
Outcome
Beta pilot with working mobile workflows for buyer matching, seller inventory management, and real-time notification delivery
NestJSBullMQPostgreSQLPrisma
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