AI engineering capacity,
where you need it.

Text, code or image generation inside the product you already ship. We deliver the feature, the evaluation set and the guardrails, then hand the repository back.

A defined workflow becomes a tool-using agent with a stop condition, an audit log and a person in the loop where a mistake is expensive.

A chatbot tied to your product and your data, with a clear line on what it will not answer. We measure it before a customer ever sees it.

Multi-turn assistants that keep context, hand off to a person and stay inside the task you scoped. Turkish and English, in the conversation you actually run.

A short engagement to decide what is worth building. You leave with a written scope, a risk list and a recommendation your own team can execute.

We work inside your repository and, when the contract says so, under your brand. Your client sees your team. You keep the relationship.

A model for a number you already track: demand, risk, churn or delay. We start from your data and a baseline, then show whether the model beats it.

Detection, classification and document vision wired into the process that needs them. You get the model, the service around it and a check for when it drifts.

Fine-tuning when a prompt and retrieval are not enough. The dataset, the eval and a comparison against the base model come with it, so you can see what the tune bought.

Choosing, hosting and wrapping a model for a real product. API, prompt layer, a cost and latency budget, and tests that fail the build when answers regress.

Grounded answers that cite the passage they used. Retrieval, reranking and an evaluation set, in Turkish and English, delivered as a working feature.

A voice agent for a bounded call: it hears, decides, calls a tool and escalates. We measure whether the task finished, not how human the voice sounds.

Classification, extraction, search and summarization over the text you already store. Tickets, PDFs and transcripts, scored so you know when the pipeline is wrong.