01 / Project case study / 2025
Gnosis AI
AI validation and planning
Turn a startup idea into a validation report, an execution plan, an interactive flowchart and a SCRUM board.
Explore the problem. Follow the system.
02 / The problem
A reason to build.
Early ideas need more than a promising score. Founders need a way to review feasibility and market assumptions, then translate the analysis into phases, dependencies and work they can track.
03 / System design
Follow the architecture.
A modular Next.js and TypeScript application integrates Groq for LLM inference, NextAuth.js for authentication and MongoDB through Mongoose for stored reports and project history. Validation results feed project planning, React Flow diagrams and SCRUM boards. Protected routes, usage tracking and access limits manage the AI workflow; the repository also supports an optional local Ollama provider.
- 01Idea
- 02Analysis
- 03Validation
- 04Execution plan
- 05Flowchart
- 06SCRUM board
04 / Engineering decisions
The choices inside.
- 01
Organize authentication, validation, project planning and dashboards as feature modules.
- 02
Turn generated analysis into editable project plans and visual task workflows.
- 03
Keep validation history behind authentication and apply usage limits to AI access.
05 / Technology
A stack with purpose.
The technologies connecting this system.
- Next.js
- React
- TypeScript
- Groq
- React Flow
- NextAuth.js
- MongoDB
- Mongoose
- Tailwind CSS
- shadcn/ui
06 / Engineering outcome
Architecture, applied.
Combines idea analysis with the practical next steps: phased plans, estimates, dependencies, flowcharts and task tracking. Reports and projects remain available in the user's validation history.