Research Library
Explore our research, benchmarks, and practical guides on enterprise AI and software.
- AI FoundationsInsightNov 3
Top 20+ Predictions from Experts on AI Job Loss
As a McKinsey consultant, I helped enterprises adopt new technologies for a decade. My quick answers: Note: The size of the plots is correlated with the size of the job loss prediction. The percentages referenced in our analysis are derived from assumptions about overall job displacement. In specific scenarios, these assumptions included potential job gains…
- E-commerce ScrapingBenchmarkNov 2
eBay Scraping: Top 7 Providers Compared
We benchmarked eBay across 5 web scraping providers, totaling 1,750 requests over search and product pages of 7 eBay country sites, measuring both success rate and end-to-end completion time. You can read more about our benchmark methodology. Bright Data, Apify and SerpApi were the three providers that returned parsed JSON. Field counts came to 59…
- Review ScrapingBenchmarkNov 2
Top 6 Amazon Review Scrapers Compared
To compare how web data scraping providers handle Amazon review extraction, we tested 5 web scraping providers on the same set of Amazon product review URLs, totaling 2,500 requests across all providers. Read our benchmark methodology for more detail on our testing process. Amazon was the most accessible platform in our reviews scraping benchmark. The…
- Scraping ToolsOpen World EvaluationNov 2
Top 11 Open Source Web Crawlers for LLM & AI
Recent advances in generative AI have reshaped what developers need from web crawlers. Agentic crawlers now use natural-language prompts to select links rather than fixed rules, and produce token-efficient markdown natively. At the same time, the classic frameworks for large-scale batch crawling remain irreplaceable for enterprise and research use. Language: Python | License: Apache 2.0…
- AI GovernanceOpen World EvaluationNov 2
Top 12 AI Governance Tools Compared
To map the AI governance landscape, we checked 12 leading platforms for their coverage of 11 core capabilities, and highlighted what each tool does best. End-to-end: Cover both sides of governance, regulatory compliance on one side and technical model testing on the other. Compliance: Handle policy, risk, and audit, but leave the technical model testing…
- LLMInsightNov 2
LLM Parameters: Types, Scaling, Fine-Tuning Guide
Parameter count is one of the most cited specifications of a large language model, but it does not determine how well a model performs or how much it costs to run. The chart below compares 31 models by their LLM Index score and their average cost per task across seven benchmarks. Four models form the…