The 4-Stage Delivery Model
We apply a structured, engineering-first process to design, build, and optimize software, intelligent systems, and research outcomes. Note that specific deliverables vary based on the nature of the engagement.
Diagnose
Understand users, requirements, existing systems, or the research question. Outputs: scope, requirements, feasibility considerations, and success criteria.
Key Deliverables:
- Technical Scoping Document
- Architecture Audit
- Literature Diagnostic
- Feasibility Report
Design
Define interfaces, architecture, data flows, agent behavior, or research methodology. Outputs: design specifications, architecture or study plan, and evaluation approach.
Key Deliverables:
- System Architecture Blueprint
- UI/UX Specifications
- AI Persona & Data Flow
- Methodology Plan
Implement
Develop the software or AI workflow, or conduct the experiments. Outputs: implementation or experimental artifacts, relevant tests, and documentation.
Key Deliverables:
- Software Artifacts
- Deployed Codebase
- AI Agent Modules
- Experimental Models
Improve
Evaluate results, resolve issues, refine performance, and prepare delivery. Outputs: evaluation findings, refinements, handover documentation, and agreed next steps.
Key Deliverables:
- Evaluation Findings
- Performance Refinements
- Technical Handover Docs
- Recommendations