Traditional AI products inject text from documents into a prompt, but Index Knowledge allows the model to develop a data extraction plan, similar to a human analyst. This is especially effective with files containing many numbers and uncommon terms, which RAG often fails to retrieve when summarizing. In a comparison against two leading document processing providers, V7 Go achieved 98% accuracy with a zero-shot approach using Index knowledge, significantly outperforming the 66% and 42% accuracy rates of the competitors.
Key takeaways:
- V7 Go's workflows break down complex tasks into reasoning steps, leading to a 32% reduction in errors over one-shot reasoning across document benchmarks.
- V7 Go is powered by Index Knowledge, a technology that breaks down large files into small searchable indexes, enabling more accurate information query than retrieval augmented generation (RAG) techniques.
- Index Knowledge utilizes the model itself to develop a data extraction plan, which is particularly effective in files containing many numbers and uncommon terms.
- V7 Go achieved 98% accuracy with a zero-shot approach using Index knowledge, significantly outperforming two leading document processing providers that achieved 66% and 42% accuracy.