AI Apps
LLM-powered product features — chat, search, generation
Embed AI directly into your product: chat copilots, semantic search, generation flows and assistive UI that turn users into power users overnight.
What you get
- In-product chat & copilots with tool calling
- Semantic & hybrid search across user data
- Streaming generation flows (text, structured, multimodal)
- Cost, latency & safety guardrails baked in
How I build it
- 1Map the user job AI should make 10× faster
- 2Pick model + fallback chain (OpenAI, Anthropic, local)
- 3Wire tools, evals & streaming UI
- 4Ship, measure cost-per-action & iterate
AI as a feature, not a product
The winning move isn't building 'an AI app' — it's adding AI to a product people already use. We embed copilots, generators and search where users already are, so adoption is automatic.
Streaming UX, not chat windows
Most 'AI features' fail because they're bolted-on chat windows. We design inline, streaming, undoable flows that feel like part of the product — not a help desk.
Cost & eval discipline
Every prompt has a cost-per-call, a latency budget and an eval set. We track all three from day one so the feature stays cheap, fast and trustworthy as it scales.
Tools & stack
Typical use cases
- SaaS copilots & in-app assistants
- Smart search & answer engines
- Content & code generation features
AI-powered social media platform with embedded LLM features for content, scheduling and analytics.