AI / ML Integration
AI embedded inside the product with LLMs, retrieval and bespoke models.
Let’s talk about this service →AI is less about being impressive in a demo and more about being reliable in production. With LLMs, retrieval (RAG) and bespoke models when needed, we build AI that truly lives inside your product — measurable and cost-controlled.
We fix retrieval first
Most bad answers come from the wrong context, not the model. We make retrieval quality measurable first.
Measure, then scale
We do not change a model without an eval set built from real examples; improvement is proven with numbers.
We control cost
We log tokens, latency and P95 to keep the product both fast and sustainable.
What we deliver.
Our stack.
Frequently asked.
Is our data used to train models?
Never without your consent. We clarify data boundaries and privacy upfront, and use self-hosted models when needed.
Isn’t adding ChatGPT enough?
Opening an interface is easy; keeping it reliable, accurate and cost-controlled in production takes engineering. That is the real work.
Should we use our own model?
In most cases off-the-shelf models + good retrieval are enough. When privacy or cost demands it, we move to self-hosted / fine-tuned models.