Personalised experience
The interface adapts to observed behaviour, so frequent actions get closer and the rest gets out of the way.
Applications that learn from how each person uses them, and hand the repetitive conversational work to a language model instead of a support queue.
A conventional app does what it was specified to do. An intelligent one observes what people actually do with it and adjusts: which screen opens first, what gets surfaced, what can be answered without a human.
We build these with current language models handling the parts that involve reading or writing natural language, and conventional engineering handling everything else. The split matters. Language models are excellent at conversation and poor at arithmetic, and pretending otherwise is how these projects fail.
The interface adapts to observed behaviour, so frequent actions get closer and the rest gets out of the way.
Routine questions answered in the app, at any hour, with escalation to a person when the model is out of its depth.
Form filling, summarising, drafting and categorising handled automatically rather than by staff.
Descriptions, replies and summaries produced on demand and reviewed rather than written from scratch.
Interactions that feel immediate, because the model runs against context the app already holds.
Clear handling of what the model does not know, which is the difference between a useful assistant and a liability.
Standard development builds defined functionality: the app does what the specification says, the same way each time. That is often exactly right, and cheaper.
The intelligent version is worth the additional cost when the value is in adapting, in handling language, or in absorbing work that currently lands on a person. If your problem is none of those, we will point you at conventional mobile development instead.
We will tell you whether a model is the right tool for it, or whether ordinary software would do the job for less.
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