Budget Allocation
A lean, pragmatic distribution across compute, data, tooling, personnel, and contingency — built to maximize academic impact per dollar.
Initiated with under $15K USD
HuskyBot is being built on a fraction of what comparable enterprise AI efforts cost — thanks to open-weight models, free academic corpora, and parameter-efficient fine-tuning. The breakdown below shows how each share is allocated by category.
Allocation by Category
Detailed Breakdown
Compute & Training
40%Cloud GPU rental for model fine-tuning, training runs, hyperparameter tuning, and evaluation benchmarks.
Data & APIs
20%API access for academic databases, data processing tools, and vector database hosting for the RAG system.
Software & Tools
17%Development tools, hosting services, monitoring solutions, and web interface deployment infrastructure.
Personnel & Training
13%Student assistant hours, training materials, documentation development, and user-guide creation.
Contingency
10%Reserved share for unexpected costs, additional compute needs, or scope adjustments during development.