ServicesProduct engineering
Custom AI Development
LLM applications, agents and pipelines built for your product and your data.
Getting an AI feature to work in a demo takes a weekend. Getting it to work for every user, within budget, without embarrassing mistakes, is engineering. We do the second part: architecture, evaluation, production hardening and a team that stays reachable after launch.
What you get
- 01
Architecture and model selection for your use case, cost and latency targets
- 02
Production LLM applications: agents, RAG pipelines, structured extraction, evaluation
- 03
Evaluation suites so quality is measured, not guessed
- 04
Deployment in your cloud with monitoring, cost controls and fallbacks
- 05
Documentation and hand-over to your team, or ongoing support from ours
How it works
Define the outcome
What the feature must do, how good is good enough, what it may cost per request. Written before we pick a model.
Prototype in two weeks
A working slice on your real data with an evaluation set. You see numbers, not promises.
Build for production
Error handling, rate limits, fallbacks, observability. The part most AI demos skip.
Ship and iterate
Staged rollout with metrics. We keep improving quality and reducing cost after launch.
Hand over or stay on
Your team gets the code and the docs. If you prefer, we stay on under a support agreement.
B2B SaaS startup
A support copilot inside the product, shipped in six weeks with a measured accuracy score.
Read the caseCommon questions
Which models do you work with?
Claude, OpenAI, Gemini and open models, chosen per task on quality, cost and data requirements. We are not tied to one vendor.
Can you work with our existing engineering team?
Yes. We plug into your repositories, reviews and sprints, and leave your team able to maintain what we built.
Do you offer white-label work for agencies?
Yes. Several agencies deliver AI projects to their clients with our team behind them.
Get a quote
Ask about custom ai development.
Describe the situation in a few lines. You get a reply from an engineer on the next business day, with an honest view on whether AI will pay back and what the first step looks like.