Dataset Engineering
We turn raw CSV or JSONL exports into clean, deduplicated, schema-validated training corpora ready for fine-tuning.
Our dataset engineering pipeline takes whatever you can export from your product, support tool, or knowledge base and shapes it into a high-quality training set.
We profile every column, fix encoding issues, normalize whitespace, deduplicate near-identical samples, and split your data into train, validation, and held-out evaluation sets. PII is detected and scrubbed by default, and we surface a transparent data report so you understand exactly what your model will learn from.
Whether you ship 500 rows or 100,000, you get the same disciplined intake process — and the same JSONL format that drops directly into OpenAI, Together AI, and Hugging Face training jobs.
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Custom Model Fine-Tuning
Fine-tune GPT, Claude, Llama, or Mistral on your dataset with hyperparameter sweeps and full training transparency.
Evaluation & Benchmarking
Measure your fine-tune against a held-out set with BLEU, ROUGE, faithfulness, and task-specific scoring.
API Endpoint Deployment
A ready-to-call REST endpoint with auth, rate limits, and a documented prompt schema you can paste into your stack.