Start with one task worth improving
An AI project needs a clear input, a useful output, and a way to check the result. We work with you to identify a bounded workflow and the people responsible for reviewing it.
Examples include an assistant that answers from approved documents, a workflow that extracts fields for review, or a system that prepares video clips for an editor. These are project scopes we can explore together.
What the work can include
Document retrieval with source references.
Structured extraction and connections to business APIs.
Agent actions with defined permissions and handoff points.
Transcription, reframing, and video processing pipelines.
Evaluation on representative examples, including failure cases.
Relevant team experience
Nuril works on LLMs, retrieval, computer vision, and model evaluation. Ayub connects AI workflows to fullstack products. Zaki builds automation and data workflows. Their profiles show the context of this experience.
Agree on how success will be checked
Bring anonymized examples of inputs and expected outputs, the tools involved, and the review steps your team needs. The proposal will define evaluation criteria and distinguish development fees from ongoing model, API, and infrastructure costs.