Production AI infrastructure for early-stage teams, shipped in weeks not quarters.
Internal AI systems & internal app buildouts: Custom schemas, data architecture, and internal tools that let your team operate with AI-native infrastructure
Agentic systems & autonomous infrastructure: Multi-step autonomous agents, guardrailed execution loops, and agent orchestration that goes beyond single-task automation
AI-native memory & retrieval architecture: Custom memory structures, RAG, and data surfacing built specifically for AI consumption
On-device deployment & predictive analytics: Local model deployment, distillation, and predictive systems for use cases where API latency, cost, or privacy makes hosted models a non-starter
Production feature sprints: Ship backlog items and codebase pushes fast
Three live products spanning AI infrastructure, full-stack AI, and vertical SaaS — pattern across architectures, not just one trick.
Educational calculus platform demonstrating production AI patterns: multi-provider LLM routing across 3 backends, RAG-based knowledge retrieval via ChromaDB, and vision-enabled tutoring over a FastAPI bridge.
Local-first AI yoga companion. Multi-provider LLM routing across 4 backends, encrypted local credential storage, and Chroma-backed pose and theme retrieval. Delivered as web, desktop, and Discord interfaces over a single Svelte + FastAPI core.
Vertical SaaS prototype for fence contractors with production-shaped architecture. Working chat-driven estimate flow, full project lifecycle, revenue dashboard, and adapter-based Stripe + email integrations typed for clean production swap.
1-week discovery, 2-week build cycles
Flat-rate sprints, not hourly billing
You own the code, I own the infrastructure
Sprints run $1.5–5K, flat-rate. Founding-customer rates while I build out public case studies; rates will rise as the portfolio fills. Larger projects scoped at a comparable rate. Quote sent within 24 hours of the intro call.
Python, TypeScript, Postgres, Supabase. Anthropic and OpenAI SDKs. Local model deployment, distillation, and predictive analytics where speed or privacy matters. Ships to production on Vercel + Supabase, the same stack most AI startups already run on, which is part of how the two-week timelines hold.