AI application
development.
AI application development is the work of integrating large language models (LLMs) into real software so they perform useful tasks — drafting, summarizing, extracting data, classifying requests or answering questions from company data. I build these features with structured outputs, cost controls and evaluation so results are reliable in production.
I add AI to products where it does real work — reading documents, drafting content, classifying requests, answering from your data — and wire it into your existing app, database and workflows rather than bolting on a chat widget.
What I build
LLM-powered features
Summaries, drafting, extraction and classification inside your product's own screens.
Document intelligence
Turn PDFs, emails and forms into structured, searchable data.
AI automations
Background jobs that process incoming work and hand exceptions to a human.
Chat and assistants
Assistants grounded in your data with streaming responses and conversation history.
Problems I solve
- AI demos that give different answers every time
- Unpredictable API bills
- Outputs that can't be trusted or parsed by the rest of the app
- No way to tell whether a prompt change made things better or worse
Technologies I use
- OpenAI API
- Anthropic Claude
- Google Gemini
- Structured outputs
- Streaming
- Python
- FastAPI
- TypeScript
- PostgreSQL + pgvector
Development process
- 01
Discovery
- 02
Architecture
- 03
Build
- 04
Test
- 05
Deploy
- 06
Iterate
Relevant projects
Technical approach
- →Structured outputs validated against a schema, so AI results are safe to store and act on.
- →Model routing — cheaper models for simple steps, stronger models only where needed.
- →Caching and rate limits to keep costs predictable.
- →A small evaluation set so prompt changes are measured, not guessed.
Frequently asked questions
Which AI model should I use?
It depends on the task, latency and budget. I usually prototype with two or three models and pick based on measured quality and cost.
Is my data sent to third parties?
Only what a feature needs. I can use providers with no-training data policies or self-hosted models via Ollama where required.
How long does a typical project take?
It depends on scope. A focused feature or fix can take days; a first production version of a product usually takes several weeks. I give a written estimate after a short discovery call.
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Ready to start
your project?
I work remotely with startups and businesses across the United States and internationally. Tell me what you're building and I'll reply with next steps.