LLM Applications

A prototype that calls a model API takes an afternoon. A production application takes engineering: outputs must be structured and validated, failures must be handled, prompts must be versioned and tested, and every call has a cost and a latency that users and finance both notice. Without that engineering, the application behaves differently every week.

Document drafting and review tools, summarisation of long records, classification and routing of incoming requests, extraction of structured data from unstructured text, translation between Arabic and English with domain terminology, and conversational interfaces over business functions.

We design the application around what the model is reliable at and protect against what it is not. Prompts and context are treated as code: versioned, reviewed and tested against an evaluation set. Outputs are structured and validated before they touch your systems. We select models per task on measured quality, cost and latency, and we keep the option to switch providers. Arabic quality is tested explicitly, not assumed.

We define the task, the inputs, the expected outputs and how quality will be judged, then build an evaluation set with your subject matter experts. The first version is built in short cycles and measured against that set. Rollout starts with a small group and widens as the numbers justify it. Monitoring of quality, cost and latency stays in place after launch.

An application your users can rely on, with the numbers to prove it.

• Production application with structured outputs, validation and fallbacks
• Versioned prompts, evaluation set and quality reports
• Cost and latency dashboard and a provider switching plan

A capability that behaves the same on Monday as it did on Friday, with a monthly cost you can forecast and a quality level you can state in writing.