Reveal high‑dim embedding behavior with an interactive 1,536‑dim PCA visualizer

Reveal high‑dim embedding behavior with an interactive 1,536‑dim PCA visualizer targets a $9.6B = 800,000 AI/ML teams/developer teams x $12,000 ARR (enterprise + mid-market tooling spend on developer/ML productivity & observability) total addressable market with medium saturation and a year-over-year growth rate of 35%+ growth in ML developer tooling & vector database adoption (2024–2027 forecast).

Key trends driving demand: Embedding commoditization -- standard embedding endpoints (OpenAI, Cohere, HF) make embedding formats portable and increase demand for tooling that inspects them.; Vector DB proliferation -- adoption of Pinecone/Weaviate/others drives need for visualization and observability layers on top of storage.; Browser GPU & WASM performance -- enables heavy linear algebra (PCA, SVD) client-side for instant UIs without sending data to servers.; Model-ops focus -- teams putting LLMs into production demand interpretability and debugging tools similar to model monitoring for ML models..