Engineer raises $100k pre-seed to build app store for AI tools in Africa

-Infra: Kubernetes + NVIDIA device plugin; 20× Jetson Nano Dev Kits

-Inference: Ollama / llama.cpp (quantized models ≤7B); token streaming (SSE/WebSocket); autoscaler driven by request queue depth + Jetson tegrastats GPU load

-Cold starts: warm-pool containers with pre-loaded quantized models (to avoid long load times on 4 GB memory)

-Networking: Envoy ingress; TLS.

-Observability: Prometheus/Grafana; structured logs; tracing.

-Billing: pay-as-you-go; mobile money (M-Pesa/Airtel); per-token + per-GPU-hour meters.

-Data: in-region storage; encrypted; no training on customer data.

-Limitations: fewer regions vs AWS; GPU supply fluctuates; docs still early.

-Roadmap: more African regions, spot-GPU pricing, fine-tune jobs.

-Ask: brutal feedback on scaling strategy + CLI UX.