AI Strategy and Discovery for Philadelphia Businesses
Most AI projects that go wrong go wrong before a single model gets trained, in the gap between what a Philadelphia business wants and what its actual data can support. We begin with a candid check on whether the data supports the ambition, not a roadmap quietly functioning as a sales pitch.
- Data readiness and quality assessment before any commitment is made
- Use-case prioritization based on real business impact, not novelty
- Build-versus-buy analysis for off-the-shelf APIs versus custom models
- A scoped technical roadmap with realistic milestones































