X-StudioServiceAI products that outlast the demo.
AI development is the work of building a product with a model at its centre: a copilot that drafts the work, an assistant that answers from your own knowledge, a tool that turns speech or documents into something structured, or a product that would not exist without a language model underneath it. We design and build these products end to end, from the first prompt to the application in your users' hands.
The hard part is rarely the model call. It is the product around it: what the model is allowed to do, how the interface shows what it did, what happens when it is wrong, and what the whole thing costs at real usage. That is where the work is, and it is design and engineering in the same thread.
Deliverables
What it covers
Applications built around a language model from day one: assistants, copilots, writing and research tools, and products whose main interaction is a conversation or a generation rather than a form.
Prompting, structured outputs, tool calling, streaming and model routing across Anthropic, OpenAI, Google and open-weight models, behind an interface your product owns so the model can change without the product changing.
Speech to text and text to speech, document understanding and image inputs, for products where the model has to read or listen before it can help.
Caching, model tiering, rate limits, guardrails and monitoring, so the product is fast for users, predictable on the invoice and safe to leave running.
How it runs
Before any product work, a short prototype against the real task with real inputs, to learn what the model does reliably and what it does not. Some ideas stop here, which is the cheapest place to stop.
Interface, data and prompts designed together, so the product leans on what the model is actually good at and the user always knows what they are looking at.
Every release is checked against an evaluation set, and production traces feed the next round of prompt, model and interface changes.
Related work
FAQ
The things people ask about this kind of engagement before the first call.
AI development is building an AI product or application end to end: the interface, the software and the model integration. AI solutions and engineering is the deeper pipeline work, such as retrieval, agents and evaluation, which can sit inside a product we build or one you already have. Most AI projects use both, and the same team does both.
Almost every product is better served by a hosted model from Anthropic, OpenAI or Google than by training one. We fine-tune or run open-weight models when data cannot leave your environment, when latency or cost demands it, or when the task is narrow enough to benefit. Either way the integration is designed so that switching models is a configuration change rather than a rebuild.
Model usage is a running cost and we treat it as a design input from the first prototype. Caching, using smaller models for simpler steps and limiting what the product sends to the model usually bring the cost per user to a number that fits the pricing. We report it alongside latency and quality throughout the build.
A working prototype against your real task usually takes one to two weeks. A first version people can use is typically eight to twelve weeks depending on scope, with releases every week from the second week and the prototype results deciding whether the build goes ahead at all.
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