From web data
to useful work.
Field guides for monitoring your market, making sense of the results and building datasets for AI.
- AI datasets
6 min readPrepare scraped datasets for a decision model with Unsloth
Use abotapi scrapers to collect reviews, create human-reviewed gold labels, prevent split leakage and prepare state, questions and gold datasets for Unsloth decision-model training.
- Marketing intelligence
5 min readFrom customer reviews to market signals: abotapi + Jev
Collect competitor reviews with abotapi, classify topics and dissatisfaction with TypeSafe AI’s Jev, and build a traceable Python market report with human review.
- Marketing intelligence
4 min readHow to monitor your market with abotapi and Python
Build a repeatable marketing monitoring workflow with abotapi scrapers, dated snapshots and Python analysis of prices, reviews and competitors.
- AI datasets
4 min readBuild an Unsloth fine-tuning dataset with abotapi scrapers
Prepare scraped web data for Unsloth fine-tuning: define a task, review rights, label examples, export JSONL and prevent evaluation leakage.
- Market analysis
3 min readCompetitor price monitoring without misleading comparisons
Use abotapi ecommerce scrapers and pandas to compare matched products, account for currencies and availability, and design reliable price alerts.
- Retrieval & agents
4 min readBuild a source-linked RAG dataset from web content
Prepare abotapi web data for retrieval: preserve sources, clean content, chunk documents, refresh indexes and evaluate grounded answers.