Our agency will build an ai training dataset with collection, cleaning, and annotation

Most AI fine-tuning projects fail before training ever starts. The dataset is incomplete, inconsistently labeled, or formatted wrong for the model. I handle the entire data pipeline from raw collection to training-ready delivery so you never have to touch a spreadsheet.

I have built and fine-tuned LLMs myself.

What You Get

Raw data collection via web scraping, public dataset curation, or GPT synthetic generation Data cleaning: deduplication, normalization, low-quality sample removal, and missing field handling Professional annotation formatted for your exact task: classification, NER, instruction-response pairs, or custom schema Dataset validation: label consistency checks, class balance analysis, and a held-out eval split Full data card documenting schema, label definitions, sample counts, and coverage statistics Final delivery in your required format: JSONL, CSV, ready to use

Why Work With Me

I have run fine-tuning pipelines with QLoRA and Unsloth. I know what makes training data produce a well-behaved model versus one that overfits or collapses. You are not hiring a labeler. You are hiring someone who understands what happens after the data is delivered