Software & AI
Most AI projects die as a demo. This one ships.
Working software, not slideware. Let me walk you through how we get from the first hello to something live. The stack and the safeguards included.
Software & AI
Working software, not slideware. Let me walk you through how we get from the first hello to something live. The stack and the safeguards included.
We start with what is slow, manual or missing, not with which model is in the headlines. The best tool is the one that quietly removes a real cost.
The fastest wins are usually the boring ones: data moving between tools, updates chased by hand, reports rebuilt every week. We map your process and automate the steps that actually eat your time.
When off-the-shelf does not fit, I build the internal tool, dashboard or app you actually need, lean and focused on the job.
For anything that has to scale, I bring in a developer and stay the one who owns the outcome.
This is where AI stops being a demo. Agents that do real tasks, and language models wired into your product with retrieval, so answers are grounded in your data, not invented.
a demo no one can trust in production is just a magic trick
The part most AI projects skip: evaluation, logging, cost controls and access rules, built in from the start so the thing is safe to put in front of real users.
Deployed, handed over with docs and access, and a clear picture of what it costs to run. I stay on call while it settles in.
Before you ask
Ship. Prototypes are easy; the value is getting something live, tested and safe to run. I build with evaluation, logging and cost controls from the start, not bolted on later.
Usually the repetitive glue work: moving data between tools, chasing updates, formatting reports. We map your process first, then automate the steps that actually cost you time.
Whatever fits the job: OpenAI, Anthropic and open models, wired into your stack with the right database and guardrails. I stay model-agnostic so you are not locked in.