Services / AI Engineering
AI engineering that ships.
On-device models, cloud LLMs, and the bridges between them.
The architectural call about what runs on-device, what runs in the cloud, and where the boundary sits — answered against your latency, cost, and privacy budget. We then wire OpenAI, Anthropic, and Gemini APIs (or Core ML, RAG over Pinecone / pgvector / Weaviate, MCP servers, SSE-streamed chat with function calling) into a shipping product, not a demo.
Core MLOpenAIAnthropicMCPRAGPineconepgvector
When it fits
Right call when…
- →You're moving from prototype to production AI features.
- →Latency, cost, and privacy push you toward hybrid architectures.
- →You need agents that actually do things, not chatbots.
Selected work
Where we've done this.
Fitness & BiomechanicsFeatured
Token-streamed AI chat client on iOS
SwiftSwiftUIVisionAsyncSequenceCombine
Fintech & Sports Analytics
Streaming LLM responses to a native iOS client
SwiftFirebaseStoreKit 2CombineSSE
Media, Audio & Communications
Structured-output ingestion from unstructured social content
SwiftSwiftUISupabaseNode.jsLLM API
Frequently asked