Use-case discovery
We pick one or two features with clear value and measurable success criteria instead of sprinkling AI everywhere.
AI integration
Practical AI inside your existing product: features your users actually use, not demos.
Building an impressive AI demo takes an afternoon. Building an AI feature that answers correctly, stays within budget, respects permissions and doesn't break when the model changes is a real engineering job.
I add AI to existing products: search and question answering over your own documents and data, assistants inside your app, and agents that automate multi-step work. I start from the user problem and the data you already have, then pick the simplest approach that works, which is often not a fine-tuned model.
Because I'm a full-stack engineer rather than a data scientist, the result is integrated into your codebase, your database and your deployment process, not a separate prototype that nobody maintains.
What you get
What's included
RAG search over your data
Embeddings in PostgreSQL with pgvector, chunking and retrieval tuned for your content, with answers that cite their sources.
In-app assistants and workflows
Chat, summarization, extraction and classification built into existing screens, respecting your users' roles and data boundaries.
AI agents
Multi-step automation with tool calling on top of the OpenAI and Claude APIs, with guardrails and human approval where it matters.
Evaluation and monitoring
Test sets, quality checks and dashboards for cost, latency and failure rates, so you know when a change makes things better or worse.
Typical stack
- OpenAI API
- Claude API
- PostgreSQL
- pgvector
- Next.js
- Laravel
- Python
FAQ
Common questions
Do I need my own model or a data science team?
Almost never. Most product features work well with hosted models from OpenAI or Anthropic plus good retrieval over your data. A data science team becomes useful much later, if at all.
How do you keep AI costs under control?
By choosing the right model per task, caching, limiting context to relevant data and tracking cost per request from day one.
Is our customers' data safe?
Retrieval is scoped to each user's permissions, and the major API providers don't train on API data by default. We review data handling against your compliance needs before launch.
Let's see if this fits your project.
Send a short brief and get an estimate within 24 hours. Not sure where to start? Begin with a code audit.