AI Systems That Reach Production, Not Just Demo

Retrieval-augmented generation grounds every answer in your actual documents, and we require source citations so an unsupported claim is visible rather than invisible. Where the system cannot find a grounded answer, it says so and escalates instead of guessing.

Local wins on data privacy, predictable cost at high volume, and no vendor lock-in, at the price of hardware and maintenance. Cloud wins on capability and zero infrastructure. We model both against your volume and requirements and give you the numbers rather than a preference.

That is the question most AI projects skip until it is a problem. We forecast token spend at projected volume during scoping, then engineer caching and model routing to reduce it. You approve a monthly figure before we build.

Yes, through authenticated API integration with your store — with scoped permissions and access controls so it can only see what a given user is entitled to see.

Self-hosting removes the third-party transfer problem, which is a large part of it. You still need a lawful basis, retention limits, and appropriate security. We build to what your counsel specifies and document the data flow.

Build cost starts around €1,500 for a focused implementation and scales with data pipeline complexity. The number that matters more is the running cost, which most projects discover too late — we forecast token spend at your projected volume during scoping and engineer caching and model routing to control it. You approve a monthly figure before we build.

Typically three to six weeks. Deploying a model against your documents is fast. The time goes into ingestion and chunking tuned to your document types, evaluation against real questions, and the guardrails that stop it answering confidently when it should escalate.

Cloud models are more capable and require no infrastructure. Self-hosted models keep data on your systems, cost predictably at high volume, and avoid vendor lock-in. For customer-facing assistants handling ordinary catalogue questions, cloud usually wins. For anything touching data that cannot leave your infrastructure, self-hosted wins regardless of capability. We model both against your volume.

No, and treating it that way is how these projects fail. A well-built assistant handles the repetitive majority — order status, product fitment, policy questions — and escalates everything else with context attached. Your team spends less time on the questions that never needed a human. The ones that did still reach one.

Not with the configurations we deploy. Business tiers of the major providers exclude API inputs from training by default, and self-hosted models never transmit data at all. We document the exact data flow for each integration so your privacy policy and any DPA request can be answered from a written record rather than an assumption.