AI services
AI & LLM systems that ship
Intelligent features for real products — not demos that die in staging. From rescue of failing AI attempts to greenfield RAG and agent workflows.
100% Job Success · Top Rated · Projects typically start from $1,000
How this engagement works
I ship LLM features the same way I ship SaaS: keys stay off the client, failures are logged, and the UI does not block first paint. OpenAI/Anthropic, FastAPI, Next.js — production, not a notebook.
Most scoped LLM features: 2–6 weeks after you approve the plan.
This is a fit if
- Founders who need an AI feature on an existing product
- Teams whose first AI attempt is stuck in staging
- Shopify brands adding search, chat, or agents without killing speed
- Agencies that need a senior to own the AI slice of a build
When to hire me for this
- You need an AI feature on a live product with server-side keys and logging
- A first AI attempt is stuck in staging or burned trust with hallucinations
- You want production habits (kill switch, cost envelope) not a notebook
01
Audit
Repo or URL. I map what is salvageable vs what to replace.
02
Architecture
Model choice, retrieval, auth, and cost envelope — in writing.
03
Build
Backend + UI with eval notes and a kill switch.
04
Handoff
Your team can operate it without me in the Slack thread forever.
What you get
- LLM API integration (OpenAI, Anthropic, and compatible providers)
- RAG over docs, catalogs, and knowledge bases
- FastAPI AI backends beside your Next.js / Node apps
- Evaluation notes to catch hallucinations early
- Secure key handling and production logging habits
Start with a free audit
Send your URL. I reply with blockers and a fixed-price path — typically under 1 hour.
Frequently asked questions
What AI technologies do you use?+
I use OpenAI API, Anthropic, LangChain, and vector databases (pgvector, Pinecone) to build AI systems that integrate with Shopify and existing web apps.
How long does an AI integration project take?+
Most projects take 2–6 weeks depending on scope, including RAG pipeline setup, prompt engineering, testing, and deployment.
Can AI chatbots handle complex customer queries?+
Yes. Using RAG (Retrieval-Augmented Generation), chatbots can access your product catalog and knowledge base to provide accurate, contextual answers.
Do you handle the FastAPI backend as well?+
Yes — I build the full stack: FastAPI AI backend, Next.js or React frontend, and the integration layer between them.
What happens if the AI project I started is not working?+
I offer AI rescue audits. Share the repo or describe what is failing and I will map the blockers and a recovery path.
Related services: RAG systems · Chatbots · Free audit
Related guides: Rescue a failed AI project · SaaS dashboard with Next.js · Add AI chatbot safely