Lilac vs Unstructured
A side-by-side look at scores, pricing and features — with RECATOOLS' ASEAN-aware verdict for each.
Lilac
Dataset curation for LLM training
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Unstructured
Open-source ETL for turning messy documents into LLM-ready data
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| RECATOOLS Score | 6.5 / 10 | 7.4 / 10 |
| Capability | ||
| Value for money | ||
| Ease of use | ||
| ASEAN readiness | ||
| API quality | ||
| Pricing | Open Source | Open Source |
| Free tier | — | — |
| Paid from | — | — |
| Has API | ✗ | ✓ |
| Open source | ✓ | ✓ |
| Free to use | ✓ | ✓ |
| Users | — | — |
| Founded | 2023 | 2022 |
| Maker | — | — |
| Verdict | Lilac is an open-source tool for exploring, clustering, searching and cleaning unstructured text datasets — useful for LLM evaluation and for preparing data for RAG, fine-tuning and pre-training. Built by ex-Google engin... |
Unstructured has become close to a default choice for the messy first step in RAG: turning PDFs, Word docs, HTML, and scanned images into clean, chunked text before embedding. The open-source Python library (Unstructured... |
| Full review → | Full review → |
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Comparisons cover up to 4 tools. Scores are RECATOOLS editorial assessments; verify current pricing on each vendor's site.