Software & AI Companies

Most start with a model-ready training dataset for one specific task, since engineering time is usually spent preparing data rather than building models. We agree the task, source data, labeling rules and quality target, then deliver a first labeled batch within a couple of weeks so your team can validate the approach before scaling.

Common sources are your product and usage data, support conversations, internal documentation and, where permitted, public or partner data relevant to your domain. We work with the data formats and storage you already use, such as cloud storage or a data warehouse, and deliver versioned releases rather than a single static file.

Expect faster model iteration because data preparation time drops, fewer quality surprises after launch because the dataset includes real and difficult cases, and an evaluation set with expert-reviewed answers so you can measure model quality objectively rather than relying on user complaints.

A first dataset or evaluation set for one task typically takes two to four weeks depending on data availability and labeling complexity. Pricing is usually based on volume and review depth, and most clients move to an ongoing refresh cycle to keep the dataset current as the product and model change.